SPM
1041
7
Health, Wellbeing and
the Changing Structure
of Communities
Coordinating Lead Authors: Guéladio Cissé (Mauritania/Switzerland/France), Robert McLeman
(Canada)
Lead Authors: Helen Adams (United Kingdom), Paulina Aldunce (Chile), Kathryn Bowen (Australia),
Diarmid Campbell-Lendrum (United Kingdom), Susan Clayton (USA), Kristie L. Ebi (USA), Jeremy
Hess (USA), Cunrui Huang (China), Qiyong Liu (China), Glenn McGregor (United Kingdom/
New Zealand), Jan Semenza (Sweden), Maria Cristina Tirado (USA/Spain)
Contributing Authors:
Ibidun Adelekan (Nigeria), Ayansina Ayanlade (Nigeria), Nicola Banwell
(Australia), Ritwika Basu (India/United Kingdom), Lea Berrang-Ford (United Kingdom/Canada),
Rachel Bezner Kerr (Canada/USA), Robbert Biesbroek (Netherlands), Halvard Buhaug (Norway),
Katrin Burkart (USA), Mercedes Bustamante (Brazil), Luisa Cabeza (Spain), Martina Angela
Caretta (Sweden), Edwin Castellanos (Guatemala), So-Min Cheong (Republic of Korea),
Winston Chow (Singapore), Mark John Costello (New Zealand/Norway/Ireland), Marlies Craig
(South Africa), Felix Creutzig (Germany), Ashlee Cunsolo (Canada), Michael Davies (United
Kingdom), David Dodman (United Kingdom), Susan Elliott (Canada), Siri Eriksen (Norway),
Maria Figueroa (Denmark/Venezuela), François Gemenne (Belgium), Elisabeth Gilmore (USA/
Canada), Bruce Glavovic (South Africa/New Zealand), Sherilee Harper (Canada), Nathalie Hilmi
(Monaco), John Ji (China), Rhys Griffith Jones (New Zealand), Felix Kanungwe Kalaba (Zambia),
Saori Kitabatake (Japan), Krishna Krishnamurthy (Mexico), Ronald Law (Philippines), Stefanie
Langsdorf (Germany), Walter Leal (Germany), Adrian Leip (Italy), Elena Lopez-Gunn (Spain/
United Kingdom), Wei Ma (China), Angelo Maggiore (Italy), Amina Maharjan (Nepal), Júlia
Alves Menezes (Brazil), Sebastian Mirasgedis (Greece), Naho Mirumachi (Japan), Ruth Morgan
(Australia), Rupa Mukerji (Switzerland/India), Aditi Mukherji (India), Virginia Murray (United
Kingdom), Jacques Andre Ndione (Senegal), Hannah Tait Neufeld (Canada), Peter Newman
(Australia), Lena Maria Nilsson (Sweden), Nick Obradovich (Germany), Ben Orlove (USA), Jennifer
J Otten (USA), Camille Parmesan (France/United Kingdom/USA), Karishma Patel (USA), Mark
Pelling (United Kingdom), Revati Phalkey (India), Elvira Poloczanska (United Kingdom), Marie-
Fanny Racault (United Kingdom/France), Diana Reckien (Germany/Netherlands), Joacim Rocklöv
(Sweden), Sharma Rohit (India), Andrea Rother (South Africa), Yamina Saheb (France/Algeria),
Sonia Salas (Chile), Gerardo Sanchez Martinez (Spain), Amiera Sawas (United Kingdom), Daniel
Schensul (USA), Corinne Schuster-Wallace (Canada), Sam Sellers (USA), Chandni Singh (India),
7
1042
Chapter 7 Health, Wellbeing and the Changing Structure of Communities
Pramod Kumar Singh (India), Yona Sipos (USA/Canada), Peter Smith (United Kingdom), Marco
Springmann (Germany), Jeff Stanaway (USA), Stavana E. Strutz (USA), Dhar Subash (Denmark/
India), Janet Swim (USA), Philip Thornton (United Kingdom), Christopher Trisos (South Africa),
Diana Urge-Vorsatz (Hungary), Maarten van Aalst (Netherlands), Jose Luis Vivero Pol (Italy), Olivia
Warrick (New Zealand), Nick Watts (Australia), Alistair Woodward (New Zealand), David Wrathall
(USA), Zinta Zommers (Latvia)
Review Editors: Bettina Menne (Italy/Germany), Sergey Semenov (Russian Federation), Jean-
François Toussaint (France)
Chapter Scientists: Christopher Boyer (USA), Nikhil Ranadive (USA)
This chapter should be cited as:
Cissé, G., R. McLeman, H. Adams, P. Aldunce, K. Bowen, D. Campbell-Lendrum, S. Clayton, K.L. Ebi, J. Hess, C. Huang,
Q. Liu, G. McGregor, J. Semenza, and M.C. Tirado, 2022: Health, Wellbeing, and the Changing Structure of Communities.
In: Climate Change 2022: Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Sixth Assessment
Report of the Intergovernmental Panel on Climate Change [H.-O. Pörtner, D.C. Roberts, M. Tignor, E.S. Poloczanska,
K. Mintenbeck, A. Alegría, M. Craig, S. Langsdorf, S. Löschke, V. Möller, A. Okem, B. Rama (eds.)]. Cambridge University
Press, Cambridge, UK and New York, NY, USA, pp. 1041–1170, doi:10.1017/9781009325844.009.
7
1043
Health, Wellbeing and the Changing Structure of Communities Chapter 7
Table of Contents
Executive Summary �������������������������������������������������������������������������������������� 1044
7.1 Introduction
����������������������������������������������������������������������������������� 1048
7.1.1 Major Health-Related Statements in AR5
������������ 1048
7.1.2 Major Statements About Migration and Conflict
in AR5
����������������������������������������������������������������������������������������� 1048
7.1.3 Important Developments Since AR5
������������������������ 1048
7.1.4 Interpretation of ‘Health and Well-Being’ Used in
This Chapter
���������������������������������������������������������������������������� 1049
7.1.5 Towards Socioecological Perspectives on Health,
Well-Being, and Loss and Damage
��������������������������� 1049
7.1.6 Developments Relevant to Tracking and Assessing
Climate Change Impacts on Health
������������������������� 1049
7.1.7 Hazards, Exposure and Vulnerability in the Context
of Human Health, Well-Being and the Changing
Structure of Communities
���������������������������������������������� 1050
Box7.1 | Indigenous Peoples’ Health and Well-Being
in a Changing Climate
����������������������������������������������������������������������� 1054
7.1.8 Visual Guide to this Chapter
��������������������������������������� 1059
7.2. Observed Impacts of Climate Change on Health,
Well-Being, Migration and Conflict
���������������������������� 1059
7.2.1 Observed Impacts on Health and Well-Being
���� 1059
Box7.2 | The Global Burden of Climate-Sensitive
Health Outcomes Assessed in this Chapter
��������������������� 1060
7.2.2 Observed Impacts on Communicable Diseases
1062
Box7.3 | Cascading Risk Pathways Linking Waterborne
Disease to Climate Hazards
���������������������������������������������������������� 1065
Cross-Chapter BoxCOVID | COVID-19
���������������������������������� 1067
7.2.3 Observed Impacts on Non-communicable
Diseases
������������������������������������������������������������������������������������ 1071
7.2.4 Observed Impacts on Other Climate-Sensitive
Health Outcomes
����������������������������������������������������������������� 1072
7.2.5 Observed Impacts on Mental Health and
Well-Being
������������������������������������������������������������������������������� 1076
7.2.6 Observed Impacts on Migration
�������������������������������� 1079
Cross-Chapter BoxMIGRATE | Climate-Related
Migration
����������������������������������������������������������������������������������������������������� 1080
Box7.4 | Gender Dimensions of Climate-Related
Migration
����������������������������������������������������������������������������������������������������� 1085
7.2.7 Observed Impacts of Climate on Conflict
������������� 1086
7.3 Projected Future Risks under Climate Change
1089
7.3.1 Projected Future Risks for Health and
Well-Being
������������������������������������������������������������������������������� 1089
7.3.2 Migration and Displacement in a Changing
Climate
��������������������������������������������������������������������������������������� 1099
Box7.5 | Uncertainties in projections of future
demographic patterns at global, regional and national
scales
��������������������������������������������������������������������������������������������������������������� 1101
7.3.3 Climate Change and Future Risks of Conflict
���� 1102
7.4 Adaptation to Key Risks and Climate Resilient
Development Pathways
������������������������������������������������������� 1102
7.4.1 Adaptation Solution Space for Health and
Well-Being
������������������������������������������������������������������������������� 1103
7.4.2 Adaptation Strategies, Policies and
Interventions
�������������������������������������������������������������������������� 1105
7.4.3 Enabling Conditions and Constraints for Health
Adaptation
������������������������������������������������������������������������������� 1115
7.4.4 Migration and Adaptation in the Context of
Climate Change
�������������������������������������������������������������������� 1116
7.4.5 Adaptation Solutions for Reducing Conflict
Risks
�������������������������������������������������������������������������������������������� 1118
7.4.6 Climate Resilient Development Pathways
����������� 1119
Cross-Chapter BoxHEALTH | Co-benefits of Climate
Actions for Human Health, Well-Being and Equity
���� 1124
Frequently Asked Questions
FAQ 7.1 | How will climate change affect physical
and mental health and well-being?
��������������������������������������� 1126
FAQ 7.2 | Will climate change lead to wide-scale
forced migration and involuntary displacement?
����� 1128
FAQ 7.3 | Will climate change increase the potential
for violent conflict?
����������������������������������������������������������������������������� 1128
FAQ 7.4 | What solutions can effectively reduce climate
change risks to health, well-being, forced migration
and conflict?
���������������������������������������������������������������������������������������������� 1128
FAQ 7.5 | What are some specific examples of actions
taken in other sectors that reduce climate change
risks in the health sector?
������������������������������������������������������������� 1129
Acknowledgements
������������������������������������������������������������������������������������� 1130
References
����������������������������������������������������������������������������������������������������������� 1130
7
1044
Chapter 7 Health, Wellbeing and the Changing Structure of Communities
Executive Summary
Climate-related illnesses, premature deaths, malnutrition in all its
forms, and threats to mental health and well-being are increasing
(very high confidence
1
). Climate hazards are a growing driver of
involuntary migration and displacement (high confidence) and are
a contributing factor to violent conflict (high confidence). These
impacts are often inter-connected, are unevenly distributed across and
within societies, and will continue to be experienced inequitably due
to differences in exposure and vulnerability (very high confidence).
Cascading and compounding risks affecting health due to extreme
weather events have been observed in all inhabited regions, and risks
are expected to increase with further warming (very high confidence)
{7.1.3, 7.1.4; Cross-Chapter BoxCOVID in Chapter 7; 7.2.1, 7.2.2, 7.2.3,
7.2.4, 7.3.1, 7.3.2, 7.3.3, 7.4.1, 7.4.4; Cross-Chapter Box HEALTH in
Chapter 7; Cross-Chapter BoxILLNESS in Chapter 2}.
Since AR5, new evidence and awareness of current impacts
and projected risks of climate change on health, well-being,
migration and conflict have emerged, including greater
evidence of the detrimental impacts of climate change on
mental health (very high confidence). New international agreements
were reached on climate change (Paris Agreement), disaster risk
reduction (DRR) (Sendai Agreement), sustainable development (the
Sustainable Development Goals (SDGs)), urbanisation (The New
Urban Agenda), migration (Global Compact for Safe, Orderly and
Regular Migration) and refugees (Global Compact on Refugees) that,
if achieved, would reduce the impacts of climate change on health,
well-being, migration and conflict (very high confidence). However, the
challenges with implementing these agreements are highlighted by
the coronavirus disease 2019 (COVID-19) pandemic, which exposed
systemic weaknesses at community, national and international levels
in the ability of societies to anticipate and respond to global risks
(high confidence). Incremental changes in policies and strategies
have proven insufficient to reduce climate-related risks to health,
well-being, migration and conflict, highlighting the value of more
integrated approaches and frameworks for solutions across systems
and sectors that are embodied in these new international agreements
(high confidence) {7.1.3, 7.2.1, 7.4.1, 7.4.2, 7.4.3, 7.4.6; Cross-Chapter
BoxCOVID in Chapter 7}.
With proactive, timely and effective adaptation, many risks
for human health and well-being could be reduced and some
potentially avoided (very high confidence). A significant adaptation
gap exists for human health and well-being and for responses to disaster
risks (very high confidence). Nationally Determined Contributions
(NDCs) to the Paris Agreement from low- and middle-income countries
identify health as a priority concern. National planning on health and
climate change is advancing, but the comprehensiveness of strategies
and plans need to be strengthened, and implementing action on
key health and climate change priorities remains challenging (high
confidence). Multi-sectoral collaboration on health and climate change
policy is evident, with uneven progress, and financial support for health
1 In this Report, the following summary terms are used to describe the available evidence: limited, medium, or robust; and for the degree of agreement: low, medium, or high. A level of confidence is
expressed using five qualifiers: very low, low, medium, high, and very high, and typeset in italics, e.g., medium confidence. For a given evidence and agreement statement, different confidence levels
can be assigned, but increasing levels of evidence and degrees of agreement are correlated with increasing confidence.
adaptation is only 0.5% of dispersed multi-lateral climate finance
projects (high confidence). This level of investment is insufficient to
protect population health and health systems from most climate-
sensitive health risks (very high confidence) {7.4.1, 7.4.2, 7.4.3}.
Climate resilient development has a strong potential to
generate substantial co-benefits for health and well-being and
to reduce risks of involuntary displacement and conflict (very
high confidence). Sustainable and climate resilient development
that decreases exposure, vulnerability and societal inequity and
that increases timely and effective adaptation and mitigation more
broadly, has the potential to reduce but not necessarily eliminate
climate change impacts on health, well-being, involuntary migration
and conflict (high confidence). This development includes greenhouse
gas (GHG) emission reductions through clean energy and transport;
climate-resilient urban planning; sustainable food systems that lead
to healthier diets; universal access to healthcare and social protection
systems; wide-scale, proactive adaptive capacity building for climate
change; and achievement of the SDGs (very high confidence). Meeting
the objectives of the Global Compact for Safe, Orderly, and Regular
Migration and building inclusive and integrative approaches to
climate-resilient peace would help prevent health risks related to
migration and conflict (high agreement, medium evidence). The net
global financial gains from these co-benefits to health and well-
being, including avoided hospitalisations, morbidity and premature
deaths, exceed the financial costs of mitigation (high confidence).
As an example of co-benefits, the financial value of health benefits
from improved air quality alone is projected to be greater than the
costs of meeting the goals of the Paris Agreement (high confidence).
All pathways to climate resilient development, including those for the
health and healthcare systems, involve balancing complex synergies
and trade-offs between development pathways and the options that
underpin climate mitigation and adaptation pathways (very high
confidence) {7.4.6; Cross-Chapter Box HEALTH in Chapter 7; Cross-
Chapter BoxMIGRATE in Chapter 7}.
Key transformations are needed to facilitate climate
resilient development pathways (CRDPs) for health, well-
being, migration and conflict avoidance (high confidence). The
transformational changes will be more effective if they are
responsive to regional, local and Indigenous knowledge and
consider the many dimensions of vulnerability, including those
that are gender- and age-specific (high confidence). A key pathway
towards climate resilience in the health sector is universal access to
primary healthcare, including mental healthcare (high confidence).
Investments in other sectors and systems that improve upon the social
determinants of health have the potential to reduce vulnerability to
climate-related health risks (high confidence). Links between climate
risks, adaptation, migration and labour markets highlight the value
of providing better mobility options as part of transformative change
(medium confidence). Strong governance and gender-sensitive
approaches to natural resource management can reduce the risk of
inter-group conflict in climate-disrupted areas (medium confidence)
7
1045
Health, Wellbeing and the Changing Structure of Communities Chapter 7
{7.4.6; Cross-Chapter Box COVID in Chapter 7; Cross-Chapter
BoxHEALTH in Chapter 7; Cross-Chapter BoxGENDER in Chapter 18;
Cross-Chapter BoxINDIG in Chapter 18; Cross-Chapter BoxMIGRATE
in Chapter 7}.
Observed Impacts
Climate hazards are increasingly contributing to a growing
number of adverse health outcomes (including communicable
and non-communicable diseases (NCDs)) in multiple geographical
areas (very high confidence). The net impacts are largely negative at
all scales (very high confidence), and there are very few examples
of beneficial outcomes from climate change at any scale (high
confidence). While malaria incidence has declined globally due to non-
climatic socioeconomic factors and health system responses, a shift to
higher altitudes has been observed as the climate warms (very high
confidence). Climate variability and change (including temperature,
relative humidity and rainfall) and population mobility are significantly
and positively associated with observed increases in dengue globally;
chikungunya virus in Asia, Latin America, North America and Europe (high
confidence); Lyme disease vector Ixodes scapularis in North America
(high confidence); and Lyme disease and tick-borne encephalitis vector
Ixodes ricinus in Europe (medium confidence). Higher temperatures (very
high confidence), heavy rainfall events (high confidence) and flooding
(medium confidence) are associated with an increase of diarrhoeal
diseases in affected regions, including cholera (very high confidence),
other gastrointestinal infections (high confidence) and food-borne
diseases due to Salmonella and Campylobacter (medium confidence).
Floods have led to increases in vector- and waterborne diseases and
to disturbances of public health services (high confidence). Climate
extremes increase the risks of several types of respiratory tract infections
(high confidence). Climate-related extreme events such as wildfires,
storms and floods are followed by increased rates of mental illness in
exposed populations (very high confidence) {7.2.1, 7.2.2, 7.2.3, 7.2.4,
7.2.5, 7.2.6}.
Several chronic, non-communicable respiratory diseases are
climate-sensitive based on their exposure pathways (e.g.,
heat, cold, dust, small particulates, ozone, fire smoke and
allergens) (high confidence), although climate change is not the
dominant driver in all cases. Worldwide, rates of adverse health
impacts associated with small particulate matter (PM) exposure have
decreased steadily due to decreasing primary emissions (very high
confidence), while rates of adverse health impacts from ozone air
pollution exposure have increased (very high confidence). Exposure to
wildland fires and associated smoke has increased in several regions
(very high confidence). Spring pollen season start dates in northern
mid-latitudes are occurring earlier due to climate change, increasing
the risks of allergic respiratory diseases (high confidence) {7.2.3.2}.
Heat is a growing health risk due to burgeoning urbanisation,
an increase in high temperature extremes and demographic
changes in countries with aging populations (very high confidence).
Potential hours of work lost due to heat has increased significantly
over the past two decades (high confidence). Some regions are already
experiencing heat stress conditions at or approaching the upper limits
of labour productivity (high confidence). A significant proportion of
warm-season heat-related mortality in temperate regions is linked
to observed anthropogenic climate change (medium confidence) but
greater evidence is required for tropical regions. For some heatwave
events over the last two decades, associated health impacts can be at
least partially attributed to observed climate change (high confidence).
Extreme heat has negative impacts on mental health, well-being,
life satisfaction, happiness, cognitive performance and aggression
(medium confidence) {7.2.4.1, 7.2.4.5}.
Climate variability and change contribute to food insecurity,
which can lead to malnutrition, including undernutrition,
overweight and obesity, and to disease susceptibility in low- and
middle-income countries (high confidence). Populations exposed
to extreme weather and climate events may consume inadequate or
insufficient food, leading to malnutrition and increasing the risk of
disease (high confidence). Children and pregnant women experience
disproportionately greater adverse nutrition and health impacts (high
confidence). Climatic influences on nutrition are strongly mediated by
socioeconomic factors (very high confidence) {7.2.4.4, 7.3.1}.
Extreme climate events act as both direct drivers (e.g.,
destruction of homes by tropical cyclones) and as indirect
drivers (e.g., rural income losses during prolonged droughts) of
involuntary migration and displacement (very high confidence).
Most documented examples of climate-related displacement occur
within national boundaries, with international movements occurring
primarily within regions, particularly between countries with
contiguous borders (high confidence). Global statistics collected since
2008 by the Internal Displacement Monitoring Centre (IDMC) show
an annual average of over 20million people internally displaced by
weather-related extreme events, with storms and floods the most
common drivers (high confidence). The largest absolute number of
people displaced by extreme weather each year occurs in Asia (South,
Southeast and East), followed by sub-Saharan Africa, but small island
states in the Caribbean and South Pacific are disproportionately affected
relative to their small population size (high confidence). Immobility in
the context of climate risks can reflect vulnerability and lack of agency
but can also be a deliberate choice of people to maintain livelihoods,
economic considerations and social and cultural attachments to place
(high confidence) {7.2.6; Cross-Chapter BoxMIGRATE in Chapter 7}.
Climate hazards have affected armed conflict within countries
(medium confidence), but the influence of climate is small
compared to socioeconomic, political and cultural factors (high
confidence). Climate increases conflict risk by undermining food
and water security, income and livelihoods in situations where there
are large populations, weather-sensitive economic activities, weak
institutions and high levels of poverty and inequality (high confidence).
In urban areas, food and water insecurity and inequitable access to
services has been associated with civil unrest where there are weak
institutions (medium confidence). Climate hazards are associated
with increased violence against women, girls and vulnerable
groups, and the experience of armed conflict is gendered (medium
confidence). Adaptation and mitigation projects implemented without
consideration of local social dynamics have exacerbated non-violent
conflict (medium confidence) {7.2.7}.
7
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Chapter 7 Health, Wellbeing and the Changing Structure of Communities
Projected Risks and Vulnerabilities
A significant increase in ill health and premature deaths from
climate-sensitive diseases and conditions is projected due to
climate change (high confidence). An excess of 250,000 deaths
yr
–1
by 2050 attributable to climate change is projected due to heat,
undernutrition, malaria and diarrhoeal disease, with more than half of
this excess mortality projected for Africa (compared to a 1961–1991
baseline period for a mid-range emissions scenario) (high confidence).
Risks for heat-related morbidity and mortality, ozone-related mortality,
malaria, diseases carried by Aedes sp. mosquitoes, Lyme disease and
West Nile fever, as well as the temperatures at which risk transitions
occur (i.e. from moderate to high to very high), are contingent on
future development pathways (high confidence) {7.3.1}.
Climate change is projected to significantly increase population
exposure to heatwaves (very high confidence) and heat-related
morbidity and mortality (high confidence). Models suggest exposure
increases 16 times under Representative Concentration Pathway
(RCP)4.5 and 36 times under RCP8.5, with the impact of warming
amplified under development pathways that do not foster sustainable
development. Globally, the impact of projected climate change on
temperature-related mortality is expected to be a net increase under
RCP4.5 to RCP8.5, even with adaptation (high confidence). Heat
related cardiovascular disease mortality is projected to increase by the
end of this century (high confidence). Strong geographical differences
in heat-related mortality are projected to emerge later this century,
mainly driven by population growth and aging in regions with tropical
and subtropical climates (very high confidence) {7.3.1}.
The burdens of several climate-sensitive food-borne, waterborne,
and vector-borne diseases (VBDs) are projected to increase under
climate change, assuming no additional adaptation (very high
confidence). The distribution and intensity of transmission of malaria is
expected to decrease in some areas and increase in others, with increases
projected mainly along the current edges of its geographic distribution
in endemic areas of sub-Saharan Africa, Asia and South America (high
confidence). Dengue risk will increase, with a larger spatio-temporal
distribution in Asia, Europe and sub-Saharan Africa under RCP6.0 and
RCP8.5, potentially putting another 2.25 billion people at risk (high
confidence). Higher incidence rates are projected for Lyme disease in
the Northern Hemisphere (high confidence) and for transmission of
Schistosoma mansoni in eastern Africa (high confidence) {7.3.1; Cross-
Chapter BoxILLNESS in Chapter 2}.
Increasing atmospheric concentrations of carbon dioxide and
climate change are projected to increase diet-related risk
factors and related non-communicable diseasess globally
and increase undernutrition, stunting and related childhood
mortality particularly in Africa and Asia, with outcomes
depending on the extent of mitigation and adaptation (high
confidence). These projected changes are expected to slow progress
towards eradication of child undernutrition and malnutrition (high
confidence). Higher atmospheric concentrations of carbon dioxide
reduce the nutritional quality of wheat, rice and other major crops,
potentially affecting millions of people at a doubling of carbon dioxide
(very high confidence) {7.3.1}.
Climate change is expected to have adverse impacts on
well-being and to further threaten mental health (very high
confidence). Children and adolescents, particularly girls, elderly people,
and people with existing mental, physical and medical challenges are
particularly at risk. Mental health impacts are expected to arise from
exposure to high temperatures, extreme weather events, displacement,
malnutrition, conflict, climate-related economic and social losses, and
anxiety and distress associated with worry about climate change (very
high confidence) {7.3.1.11}.
Future climate-related migration is expected to vary by region
and over time, according to future climatic drivers, patterns of
population growth, adaptive capacity of exposed populations
and international development and migration policies (high
confidence). The wide range of potential outcomes is reflected in model
projections of population displacements by 2050 in Latin America, sub-
Saharan Africa and south Asia due to climate change, which vary from
31 million to 143 million people, depending on assumptions about
future GHG emissions and socioeconomic development trajectories
(high confidence). With every additional one degree Celsius of
warming, the global risks of involuntary displacement due to flood
events are projected to rise by approximately 50% (high confidence).
High emissions/low development scenarios raise the potential
for higher levels of migration and involuntary displacement (high
confidence) and increase the need for planned relocations and support
for people exposed to climate extremes but lacking the means to move
(high confidence) {7.3.2; Cross-Chapter BoxMIGRATE in Chapter 7}.
Climate change may increase susceptibility to violent conflict,
primarily intra-state conflicts, by strengthening climate-sensitive
drivers of conflict (medium confidence). Future violent conflict risk
is highly mediated by socioeconomic development trajectories (high
confidence) and so trajectories that prioritise economic growth,
political rights and sustainability are associated with lower conflict risk
(medium confidence). Future climate change may exceed adaptation
limits and generate new causal pathways not observed under current
climate variability (medium confidence). Economic shocks are not
included in many models of conflict risks currently used, and some
projections do not incorporate known socioeconomic predictors of
conflict (medium confidence). As such, future increases in conflict-
related deaths with climate change have been estimated, but results
are inconclusive (medium confidence).
Solutions
Since AR5, the value of cross-sectoral collaboration to advance
sustainable development has been more widely recognised,
but despite acknowledgement of the importance of health
adaptation as a key component, action has been slow (high
confidence). Building climate-resilient health systems will require
multi-sectoral, multi-system and collaborative efforts at all governance
scales (very high confidence) (Sections7.4.1, 7.4.2). Globally, health
systems are poorly resourced in general, and their capacity to
respond to climate change is weak, with mental health support being
particularly inadequate (very high confidence). The health sectors of
some countries have focused on implementing incremental changes to
policies and measures to fill the adaptation gap (very high confidence).
7
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Health, Wellbeing and the Changing Structure of Communities Chapter 7
As the likelihood of dangerous risks to human health continue to
increase, there is greater need for transformational changes to health
and other systems (very high confidence). This highlights an urgent
and immediate need to address the wider interactions between
environmental change, socioeconomic development and human health
and well-being (high confidence) {7.4.1, 7.4.2, 7.4.3}.
Targeted investments in health and other systems, including
multi-sectoral, integrated approaches to protect against key
health risks can effectively increase resilience (high confidence).
Increased investment in strengthening general health systems, along
with targeted investments to enhance protection against specific
climate-sensitive exposures (e.g., hazard early warning and response
systems, and integrated vector control programmes for VBDs) will
increase resilience if implemented to at least keep pace with climate
change (high confidence).
The future effects of climate change on VBDs can be significantly
offset through enhanced commitment to and implementation
of integrated vector control management approaches, disease
surveillance, early warning systems and vaccine development (very
high confidence) (Sections7.4.1, 7.4.2).
Adaptation options for future climate risks associated with
waterborne and food-borne diseasess include improving access
to potable water, reducing exposure of water and sanitation
systems to flooding and extreme weather events, and improved
(including expanded) early warning systems (very high confidence)
(Sections7.4.1, 7.4.2).
Adaptation options for future extreme heat risks include heat
action plans (HAPs) that incorporate early warning and response
systems for urban and non-urban settings; tried, tested and
iteratively updated response strategies targeting both the general
population and vulnerable groups such as older adults or outside
workers; and effective stakeholder communication plans (high
confidence). These short-term responses can be complemented by
longer-term urban planning and design, including nature-based
solutions (NbS) that mitigate urban heat island (UHI) effects (high
confidence) (Sections7.4.1, 7.4.2, 7.4.3).
Adaptation options to reduce the future risks of malnutrition
include access to healthy, affordable, diverse diets from sustainable
food systems (high confidence); health services including maternal,
child and reproductive health (high confidence); nutrition services,
nutrition and shock sensitive social protection (high confidence);
water, sanitation and early warning systems (high confidence); and
risk reduction schemes such as insurance (medium confidence)
(Section7.4.2.1.3).
The COVID-19 pandemic has demonstrated the value of
coordinated and multi-sectoral planning, social protection
systems, safety nets and other capacities in societies to cope
with a range of shocks and stresses (high confidence). The
pandemic has posed a severe shock to many socioeconomic systems,
resulting in substantial changes in vulnerability and exposure of
people to climate risks (high confidence). The pandemic emphasises
the inter-connected and compound nature of risks, vulnerabilities, and
responses to emergencies that are simultaneously local and global
(high confidence). Pathways to climate resilient development can be
pursued simultaneously with recovering from the COVID-19 pandemic
(high confidence). The COVID-19 pandemic has aggravated climate
risks, demonstrated the global and local vulnerability to cascading
shocks and illustrated the importance of integrated solutions that
tackle ecosystem degradation and structural vulnerabilities in human
societies (high confidence) {Cross-Chapter BoxCOVID in Chapter 7}.
Transitioning towards equitable, low-carbon societies has
multiple benefits for health and well-being (very high confidence).
Benefits for health and well-being can be gained from wide-spread,
equitable access to affordable renewable energy (high confidence);
active transport (e.g., walking and cycling) (high confidence); green
buildings and nature-based solutions, such as green and blue urban
infrastructure (high confidence); and by transitioning to a low-carbon,
well-being-oriented and equity-oriented economy consistent with the
aims of the SDGs (high confidence). Plant-rich diets consistent with
international recommendations for healthy diets could contribute to
lower GHG emissions while also generating health co-benefits, such
as reducing ill health related to over-consumption of animal-based
products (high confidence) {7.4.2; Cross-Chapter Box HEALTH in
Chapter 7; 7.4.4}.
Reducing future risks of involuntary migration and displacement
due to climate change is possible through cooperative
international efforts to enhance institutional adaptive capacity
and sustainable development (high confidence). Institutional and
cross-sectoral efforts to build adaptive capacity, coupled with policies
aimed at ensuring safe and orderly movements of people within and
between states, can form part of the CRDPs that reduce future risks
of climate-related involuntary migration, displacement and immobility
(medium confidence). In locations where permanent, government-
assisted relocation becomes unavoidable, active involvement of local
populations in planning and decision-making increases the likelihood
of successful outcomes (medium confidence). People who live on small
island states do not view relocation as an appropriate or desirable
means of adapting to the impacts of climate change (high confidence)
{7.4.3; Cross-Chapter BoxMIGRATE in Chapter 7}.
Adaptation and sustainable development build peace in conflict-
prone regions by addressing the drivers of grievances that lead
to conflict and vulnerability to climate change (high confidence).
Environmental peacebuilding (EP) through natural resource sharing,
conflict-sensitive adaptation and climate-resilient peacebuilding offer
promising avenues for addressing conflict risk, but their efficacy is still
to be demonstrated through effective monitoring and evaluation (high
confidence). Formal institutional arrangements for natural resource
management contribute to wider cooperation and peacebuilding
(high confidence) and gender-based approaches provide under-utilised
pathways to achieving sustainable peace (medium confidence).
Inclusion, cross-issue and cross-sectoral integration in policy and
programming, and approaches that incorporate different geographical
scales and work across national boundaries can support climate-
resilient peace (high confidence) {7.4.5, 7.4.6}.
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Chapter 7 Health, Wellbeing and the Changing Structure of Communities
7.1 Introduction
This chapter assesses peer-reviewed and selected grey literature
published since the IPCC’s Fifth Assessment Report (AR5) on the
impacts and projected future risks of climate change for health, well-
being, migration and conflict, taking into consideration determinants
of vulnerability and the dynamic structure of human populations and
communities. Particular attention is given to potential adaptation
challenges and actions as well as potential co-benefits for health
associated with mitigation actions. AR5 presented strong evidence-
based statements regarding the likely
2
impacts of climate change on
health, migration and conflict in two separate chapters on Human Health
(Chapter 11) and Human Security (Chapter 12). The present chapter
covers all topics found in AR5 Chapter 11 and Sections12.4 (Migration
and Mobility Dimensions of Human Security), 12.5 (Climate Change and
Armed Conflict) and 12.6 (State Integrity and Geopolitical Rivalry) and
provides an additional, expanded assessment of mental health impacts,
gender dimensions of climate risks and solution pathways.
7.1.1 Major Health-Related Statements in AR5
AR5 stated with very high confidence that the health of human
populations is sensitive to climate change (Smith et al., 2014).
Specific observations of current impacts included the expansion of the
geographical ranges of some diseases into previously unaffected areas
and changes in the distributions of some food-, water- and vector-
borne diseases (high confidence). Increasing future health risks were
projected from injury, disease and death due to more intense heatwaves
and fires (very high confidence), undernutrition in poor regions (high
confidence), food- and waterborne diseases (very high confidence)
and VBDs (medium confidence). AR5 found that climate change is a
multiplier of existing health vulnerabilities, including food insecurity
and limited access to safe water, improved sanitation, healthcare and
education, and that the most effective measures to reduce vulnerability
in the near term are programmes that implement and improve basic
public health (very high confidence). Opportunities for co-benefits from
mitigation actions were identified through such actions as reducing
local emissions of short-lived climate pollutants from energy systems
(very high confidence) and expanding transport systems that promote
active travel (high confidence). The significant growth in peer-reviewed
publications on links between climate change and human health and
well-being since AR5 allowed for a more detailed and wider reaching
assessment in the present chapter and stronger confidence statements
for many climate-sensitive health outcomes.
7.1.2 Major Statements About Migration and Conflict in
AR5
Key statements made in AR5 Chapter 12 (Human Security) about the
impacts of climate change on migration were that climate change
will have significant impacts on forms of migration that compromise
2 In this Report, the following terms have been used to indicate the assessed likelihood of an outcome or a result: Virtually certain 99–100% probability, Very likely 90–100%, Likely 66–100%, About as
likely as not 33–66%, Unlikely 0–33%, Very unlikely 0–10%, and Exceptionally unlikely 0–1%. Additional terms (Extremely likely: 95–100%, More likely than not >50–100%, and Extremely unlikely
0–5%) may also be used when appropriate. Assessed likelihood is typeset in italics, e.g., very likely). This Report also uses the term ‘likely range’ to indicate that the assessed likelihood of an outcome
lies within the 17–83% probability range.
human security and that mobility is a widely used strategy to maintain
livelihoods in response to social and environmental changes (high
agreement, medium evidence). Research on the influence of climate
change and climate extremes on multiple forms of migration (including
voluntary migration, involuntary displacement and immobility) has
expanded significantly since AR5, which has allowed for a more robust
assessment in this chapter, with migration also featuring in most other
sectoral and regional chapters of this report. With respect to violent
conflict, AR5 Chapter 12 found that people living in places affected by
violent conflict are particularly vulnerable to climate change (medium
evidence, high agreement), that some of the factors increasing the risk
of violent conflict within states are sensitive to climate change (medium
evidence, medium agreement) and that climate change will lead to
new challenges to states and will increasingly shape both conditions
of security and national security policies (medium evidence, medium
agreement). As with other subjects assessed in this chapter, there
has been significant growth in the number of assessable studies, but
there remain shortcomings with respect to the availability of evidence
regarding the specific nature of causal linkages and the attributability
of particular outcomes to climate events or conditions.
7.1.3 Important Developments Since AR5
7.1.3.1 International Agreements
Since AR5, several new international agreements have come into
effect that have implications for international responses to the
climate risks assessed in this chapter. The 2015 Paris Agreement,
which explicitly mentions health in three separate sections, set new
goals for adaptation and established a working group to study the
effects of climate change on population displacement. The 17 United
Nations (UN) SDGs for 2030, adopted in 2015, are all important for
building adaptive capacity in general, with goals 13 (‘Take urgent
action to combat climate change and its impacts’) and 3 (‘Ensure
healthy lives and promote well-being for all at all ages’) being directly
relevant to this chapter. Other SDGs contain specific targets that are
also relevant for this chapter, including Target 10.7 (‘Well-managed
migration policies’), Target 8.3 (‘Decent work for all’) and Target 5.4
(‘Promotion of peaceful and inclusive societies’) (Piper, 2017). The
2015 Sendai Framework for Disaster Risk Reduction puts an emphasis
on health and well-being (Aitsi-Selmi and Murray, 2016) In 2018, UN
member states negotiated Global Compacts for Safe, Orderly and
Regular Migration and on Refugees that, taken together with the Paris
Agreement, provide pathways for coordinated international responses
to climate-related migration and displacement (Warner, 2018).
7.1.3.2 IPCC Special Reports
All three post-AR5 IPCC Special Reports considered some of the
research that is assessed here in greater detail. The 2018 report on
1.5°C (SR1.5) included a review of climate change and health literature
published since AR5 and called for further efforts for protecting health
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Health, Wellbeing and the Changing Structure of Communities Chapter 7
and well-being of vulnerable people and regions (Ebi etal., 2018b)
and highlighted links between climate change hazards, poverty, food
security, migration and conflict. The 2019 Special Report on Climate
Change and Land (SRCCL) (IPCC, 2019b) emphasised the impacts of
climate change on food security; highlighted links between reduced
resilience of dryland populations, land degradation, migration and
conflict; and raised concerns about the impacts of climate extremes.
The 2019 Special Report on the Ocean and Cryosphere in a Changing
Climate (IPCC, 2019a) detailed how changes in the cryosphere
and ocean systems have impacted people and ecosystem services,
particularly food security, water resources, water quality, livelihoods,
health and well-being, infrastructure, transportation, tourism and
recreation as well as the culture of human societies, particularly for
Indigenous Peoples. It also noted the risks of future displacements due
to rising sea levels and associated coastal hazards.
7.1.4 Interpretation of ‘Health and Well-Being’ Used in
This Chapter
Assessing the links between human health, well-being and climate
change is a new task for AR6, reflecting a broad perspective on health
that increasingly acknowledges the importance of well-being and its
interactions with individual and population health. The World Health
Organization (WHO) defines health as ‘a state of complete physical,
mental and social well-being and not merely the absence of disease or
infirmity’ (WHO, 1946). Although this chapter assesses physical health,
mental health and general well-being separately, they are inter-
connected; any type of health problem can reduce overall well-being
and vice versa. For example, a child receiving inadequate nutrition may
not be sick but is experiencing a clear threat to well-being that has
implications for future physical and mental health.
There is no consensus definition of well-being, but it is generally agreed
that it includes a predominance of positive emotions and moods (e.g.,
happiness) compared with extreme negative emotions (e.g., anxiety),
satisfaction with life, a sense of meaning and positive functioning,
including the capacity for unimpaired cognitive functioning and
economic productivity (Diener and Tay, 2015; Piekałkiewicz, 2017).
A capabilities approach (Sen, 2001) focuses on the opportunity for
people to achieve their goals in life (Vik and Carlquist, 2018) or the
ability to take part in society in a meaningful way, and is reflected
in personal freedoms, human agency, self-efficacy, ability to self-
actualise, dignity and relatedness to others (Markussen etal., 2018).
An indigenous perspective on well-being is broad and typically
incorporates a healthy relationship with the natural world (Sangha
etal., 2018); emotional and mental health have also been linked to
a strong cultural identity (Butler etal., 2019; Dockery, 2020). ‘Health’
itself is sometimes described as including relationships between
humans and nature as well as links to community and culture
(Donatuto etal., 2020; Dudgeon etal., 2017).
Subjective well-being is consistently associated with personal indicators
such as higher income, greater economic productivity, better physical
health (Diener and Tay, 2015; Delhey and Dragolov, 2016; De Neve
etal., 2013) and environmental health, and it is reflected in societal
indicators such as social cohesion and equality (Delhey and Dragolov,
2016). In a global survey of over 1 million people taken between
2004 and 2008 via the Gallup World Poll, annual income and access
to food were strong predictors of subjective well-being and a healthy
environment. In particular, access to clean water was important even
when household income was controlled (Diener and Tay, 2015). Access
to green spaces was also closely associated with well-being (high
confidence) (Lovell etal., 2018; Yuan etal., 2018).
7.1.5 Towards Socioecological Perspectives on Health,
Well-Being, and Loss and Damage
Since AR5, more comprehensive frameworks for framing and studying
global health issues, including planetary health, ‘One Health’ and eco-
health, have gained traction. These frameworks share an ecological
perspective, emphasise the role of complex systems and highlight the
need for inter-disciplinary approaches related to human health research
and practice (Lerner and Berg, 2015; Zinsstag etal., 2018; Whitmee
et al., 2015; Steffen et al., 2015). These frameworks increasingly
shape the evidence related to climate change health impacts and
response options, highlight the dynamics of complex systems in risk
management and direct risk management efforts in new directions.
Building on these frameworks and perspectives, there is increasing
overlap in the literature on global health, climate change impacts and
estimates of loss and damage. The Global Burden of Disease study
for 2019 for the first time included non-optimal temperature as a
risk factor (Murray etal., 2020). Work by social scientists continues
to explore how climate change indirectly affects resource availability,
productivity, migration and conflict (Burke etal., 2015a; Carleton and
Hsiang, 2016; Hsiang etal., 2017), bringing multiple lines of inquiry
together to study the associations between global environmental
changes, socioeconomic dynamics and impacts on health and well-
being. Morbidity associated with migration and displacement,
especially in the context of small island states, has been identified as
a non-material form of loss and damage (Thomas and Benjamin, 2020;
McNamara etal., 2021). Social costs of carbon estimates have been
updated to include excess mortality associated with climate change,
increasing estimates substantially (Dressler, 2021).
7.1.6 Developments Relevant to Tracking and Assessing
Climate Change Impacts on Health
Since AR5, there has been a steady increase in standardised, globally
scoped, data-driven health impact assessments, such as the ongoing
Global Burden of Disease study (James etal., 2018) that now includes
scenario-based projections (Foreman etal., 2018), that make linkages
with other global priorities, including the SDGs (Fullman etal., 2017).
Attention has turned from prioritising specific diseases like HIV/
AIDS, malaria and tuberculosis, to strengthening health systems
and providing universal health coverage (Chang et al., 2019), with
an ongoing emphasis on the social determinants of health. Several
climate-sensitive health outcomes are now tracked in the annual
Lancet Countdown reports (Watts etal., 2015; Watts etal., 2017; Watts
etal., 2018b; Watts etal., 2019; Watts etal., 2021). The Global Burden
of Disease study is beginning to examine climate-sensitive disease
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Chapter 7 Health, Wellbeing and the Changing Structure of Communities
burdens, incorporate temperature as a risk factor (Murray etal., 2020)
and project future cause-specific disease burdens in a warming world
(Burkart et al., 2021). Although not assessed in this chapter, there
are numerous ongoing assessments of climate change impacts on
health and well-being being undertaken by national and local health
authorities that continue to generate insights into climate-related
health impacts and suggest response options relevant for decision
makers.
While the knowledge base regarding global health has increased, a
comprehensive framework is not in place that fully integrates health,
well-being and environmental impacts from climate change allowing
for the cumulative assessment of their impact. Moreover, significant
cracks in the foundation of global health governance that affect
preparedness and adaptive capacity for climate change, among other
threats, have been identified (Phelan etal., 2020; Defor and Oheneba-
Dornyo, 2020; Ostergard etal., 2020; Shaffie, 2021). While attention
to climate change and health has increased and there is evidence of
increasing adaptation activity in the health sector (Watts etal., 2019),
there is also continued evidence of substantial adaptation gaps (UNEP,
2018; UNEP, 2021) including gaps in humanitarian response capacity
for climate-related disasters (Watts et al., 2021) that appear to be
widening as adverse climate change impacts on health and well-being
accrue.
7.1.7 Hazards, Exposure and Vulnerability in the Context
of Human Health, Well-Being and the Changing
Structure of Communities
7.1.7.1 Possible Climate Futures and Hazards
This chapter uses the conceptual framing described in Chapter 1, in
which risks emerging from climate change are described in terms
of hazard, exposure and vulnerability, with adaptation and climate
resilient development being responses that have the potential to
reduce or modify risk. The observed and projected future risks to
health well-being, involuntary population displacements and conflict
identified in this chapter are associated with a range of hazards that
are manifested at a variety of geographical and temporal scales. These
include observed and projected changes in climate normals; changes
in the frequency, duration, and/or severity of extreme events; and
hazards such as rising sea levels and extreme temperatures where the
impacts have only begun to be widely experienced. The 2021 report
of IPCC WGI (IPCC, 2021) provides an assessment of observed and
projected changes in these hazards and is the backdrop against which
assessments of future risks and adaptation options identified in the
present chapter should be considered.
The exposure to hazards of populations, infrastructure, ecosystem
capital, socioeconomic systems and cultural assets critical to health
and well-being varies considerably across and within regions (high
confidence). Exposure is also projected to vary across and within
regions over time, depending on future GHG emissions pathways,
development trajectories and differential vulnerability, particularly for
exposure to extreme events and conditions, such as floods and droughts
(Figures7.1a, 7.1b) (Winsemius etal. 2018). For this reason, region-
specific assessments of climate-related risks for health, displacement
and conflict are found in each of the regional chapters of this report in
addition to the general assessment that appears in this chapter.
7.1.7.2 Differential Vulnerability and Cascading Effects
Vulnerability to climate change varies across time and location,
across communities, and among individuals within communities; it
reflects variations and changes in macro-scale non-climatic factors
(such as changes in population, economic development, education,
infrastructure, behaviour, technology and ecosystems) and individual-
or household-specific characteristics, such as age, socioeconomic
status, access to livelihood assets, pre-existing health conditions and
ability (US Global Change Research Program, 2016; Chapter 1).
Many direct and indirect effects of climate change pose multiple
threats to human health and well-being and can occur simultaneously,
resulting in compounding or cascading impacts for vulnerable
populations. For example, many of the long-term impacts of climate
change on NCDs and injury described in Sections 7.2 and 7.3 are
associated with future increases in air temperature and levels of air
pollution; in many regions, and especially in large urban centres in Asia
and Africa, these particular hazards are already causing substantial
increases in morbidity and mortality due to respiratory illnesses (Tong
etal., 2016). Climate change can therefore be expected to magnify
such health risks over the long term.
At the same time, urban populations will also be experiencing indirect
risks through climate change impacts on food and potable water
systems, variations in the distribution and seasonality of infectious
diseases and growing demand for shelter due to increased in-
migration. The accumulation of these risks over time can be expected
to generate accelerating declines in community resilience and health,
with future vulnerability potentially expanding in a nonlinear fashion
(Dilling etal., 2017; Liang and Gong, 2017; El-Zein and Tonmoy, 2017;
see also Chapter 6). Further, although each individual risk in isolation
may be transitory or temporary for the individuals or groups exposed,
taken cumulatively, the impacts could create conditions of chronic
lack of well-being, and early life experiences with specific illnesses
and conditions could have lifelong consequences (Watts etal., 2015;
Otto etal., 2017; WHO, 2018a). In this context, there is a distinct need
for greater longitudinal research on vulnerability to multiple climatic
and non-climatic health and well-being hazards over time (Fawcett
etal., 2017). There is also need for more research to identify critical
thresholds in social vulnerability to climate change (Otto etal., 2017);
these include rapid, stepwise changes in vulnerability that emerge
from changes in exposure (for example, air temperatures above which
mortality rates or impacts on pre-natal health accelerate (Arroyo
etal., 2016; Ngo and Horton, 2016; Abiona, 2017; Auger etal., 2017;
Molina and Saldarriaga, 2017; Zhang etal., 2017b)) and thresholds in
adaptation processes (such as when rural out-migration rates grow
due to climate-related crop failures (McLeman, 2017)).
In virtually all of the research identifying particular climate-related
risks to health, well-being, migration and conflict, specific types of
individuals are identified as having higher levels of vulnerability
and exposure to climate-related health hazards: people who are
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Health, Wellbeing and the Changing Structure of Communities Chapter 7
impoverished, undernourished, struggle with chronic or repeated
illnesses, live in insecure housing in polluted or heavily degraded
environments, work in unsafe conditions, are disabled, have limited
education and/or have poor access to health and social infrastructure
(WHO, 2018a). Their disproportionate exposure to ongoing climate
hazards and their inability to recover from extreme events increase
not only their own vulnerability but also that of the wider communities
in which they live (US Global Change Research Program, 2016).
Highly vulnerable populations are not evenly distributed across
regions (Figure 7.2) nor within countries. Yet, even those fortunate
enough to live in better neighbourhoods with greater financial means,
higher-paying jobs and good access to resources and services, may
experience adverse climate-related outcomes through community-level
interactions and linkages (Haines and Ebi, 2019). Increased inequity
itself threatens well-being and an effective response to climate change
should not only avoid increased inequity but identify ways in which to
reduce existing inequity.
7.1.7.3 Heightened Vulnerability to Climate-Related Impacts on
Health and Well-Being Experienced by Specific Groups
and Through Specific Pathways
7.1.7.3.1 Women and Girls
Climate change poses distinct risks to women’s health. Vulnerability
to climate-related impacts on health and well-being shows notable
differentiations according to gender, beyond implications for pregnant
women. In many societies, differential exposure to such risks relate
to gendered livelihood practices and mobility options. Pregnancy and
maternal status heighten vulnerability to heat, infectious diseases,
food-borne infections and air pollution (Arroyo et al., 2016; Ngo
and Horton, 2016; Zhang etal., 2017b). Extreme heat events, high
ambient temperatures, high concentrations of airborne particulates,
water-related illnesses and natural hazards are associated with higher
rates of adverse pregnancy outcomes such as spontaneous abortion,
stillbirth, low birth weight and pre-term birth (Arroyo et al., 2016;
Ngo and Horton, 2016; Abiona, 2017; Auger et al., 2017; Molina
and Saldarriaga, 2017; Zhang etal., 2017b). Women and girls are at
greater risk of food insecurity (FAO, 2018; Alston and Akhter, 2016),
which is particularly problematic in combination with the nutritional
<-50%
>50%
15–25%
-5– 5%
-25– -15%
25–50%
5–15%
-15– -5%
-50– -25%
(b) Projected exposure of poor people to droughts.
Exposure
increase
RCP8.5
2050
Projected exposure of poor people to floods and droughts in selected regions
by 2050 under a high emissions scenario (RCP8.5)
(a) Projected exposure of poor people to floods.
Central and South AmericaAsiaAfrica
Central and South AmericaAsiaAfrica
Figure7.1 | Projected exposure of poor people to a) floods respectively b) droughts in selected regions by 2050 under a high emissions scenario (RCP8.5)
(adapted from Winsemius et al., 2018).
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Chapter 7 Health, Wellbeing and the Changing Structure of Communities
(a)
Vulnerability at the national level varies. Vulnerability also greatly differs within countries.
Countries with moderate or low average vulnerability have sub-populations with high vulnerability and vice versa.
Relative vulnerability
Medium
Very high
Low
Very low
Population density
Low
High
Observed human vulnerability to climate change is a key risk factor and differs globally
High
Children in rural low-income communities | food insecurity, sensitivity to undernutrition and
disease | 5.12.3
People uprooted by conflict in the Near East and Sahel | prolonged temporary status, limited
mobility | Box 8.1, Box 8.4
Women & non-binary | limited access to & control over resources, e.g. water, land, credit |
Box 9.1, CCB-GENDER, 4.8.3, 5.4.2, 10.3.3
Migrants | informal status, limited access to health services & shelter, exclusion from
decision-making processes | 6.3.6, Box 10.2
Aboriginal and Torres Strait Islander Peoples | poverty, food & housing insecurity,
dislocation from community | 11.4.1
People living in informal settlements | poverty, limited basic services & often located in areas
with high exposure to climate hazards | 6.2.3, Box 9.1, 9.9, 10.4.6, 12.3.2, 12.3.5, 15.3.4
Examples of
Indigenous Peoples with
high vulnerability to
climate change and
climate change responses
(4.3.8, 5.10.2, 5.13.5,
Box7.1, 8.2.1, 15.6.4) and
the importance of
Indigenous Knowledge
(Box9.2.1, 11.4, 14.4,
Cross-Chapter Box INDIG)
Indigenous Peoples of the Arctic | health inequality, limited access to subsistence resources and
culture | CCP 6.2.3, CCP 6.3.1
Urban ethnic minorities | structural inequality, marginalisation, exclusion from planning processes
| 14.5.9, 14.5.5, 6.3.6
Smallholder coffee producers | limited market access & stability, single crop dependency, limited
institutional support | 5.4.2
Indigenous Peoples in the Amazon | land degradation, deforestation, poverty, lack of support |
8.2.1, Box 8.6
Older people, especially those poor & socially isolated | health issues, disability, limited access
to support | 8.2.1, 13.7.1, 6.2.3, 7.1.7
Island communities | limited land, population growth and coastal ecosystem degradation | 15.3.2
Examples of vulnerable local groups across different contexts include the following:
Africa
North America
Central &
South America
Australasia
Small islands
Europe
Small islands
Asia
Small islands
1
3
4
2
5
6
7
8
9
10
11
12
7
8
9
12
9
1
10 12
8
12
3
4
3
6 12
1
2
1
5
3
6 12
11
3
6 12
Figure7.2 | Global distribution of vulnerable people from two indices, with examples (see also Technical Summary, this report).
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Health, Wellbeing and the Changing Structure of Communities Chapter 7
needs associated with pregnancy or breastfeeding. Women and girls
are more likely to die in extreme weather events (Garcia and Sheehan,
2016; Yang etal., 2019). Women are also expected to face a greater
mental health burden in a changing climate (Manning and Clayton,
2018). Further, climatic extremes and water scarcity are associated
with increases in violence against girls and women (Anwar etal., 2019;
Opondo etal., 2016; Le Masson etal., 2016; Udas etal., 2019).
7.1.7.3.2 Children
Children are particularly vulnerable to climate change impacts.
Children often have unique pathways of exposure and sensitivity to
climate hazards, given their immature physiology and metabolism
and high intake of air, food and water relative to their body weight
as compared with adults (US Global Change Research Group, 2016).
Climate change is expected to increase childhood risks of malnutrition
and infectious disease for children in low-income countries through its
impacts on household food access, dietary diversity, nutrient quality,
water and changes in maternal and childcare access and breastfeeding
(Tirado, 2017; FAO et al., 2018; Perera, 2017). Children living in
locations with poor sanitation are especially vulnerable to GI illnesses,
with future rates of diarrhoeal diseases among children expected to
rise under many climate change scenarios (Cissé etal., 2018; WHO,
2014). Outdoor recreational opportunities for children may be reduced
by extreme weather events, heat and poor air quality (Evans, 2019).
Children and adolescents are particularly vulnerable to post-traumatic
stress after extreme weather events; the effects may even be long-
lasting, with impacts on their adult functioning (Brown etal., 2017;
UNICEF, 2021; Thiery etal., 2021)
7.1.7.3.3 Elderly
Population age structures and changes over time have a significant
influence on vulnerability to the impacts of weather and climate.
Older adults (generally defined as persons aged 65 and older) are
disproportionately vulnerable to the health impacts associated with
climate change and weather extremes, including a greater risk of
succumbing to waterborne pathogens due to poorer functioning
thermoregulatory mechanisms, greater sensitivity to dehydration,
changes in their immune systems and greater likelihood of having pre-
existing chronic illnesses such as diabetes or respiratory, cardiovascular
and pulmonary illnesses (Benmarhnia etal., 2016; Diaz etal., 2015;
Mayrhuber etal., 2018; Paavola, 2017). Older adults may be less prompt
in seeking medical attention when suffering from GI illnesses, which
can lead to dehydration (Haq and Gutman, 2014). Åström etal. (2017)
anticipate heat-related mortality among the elderly in Europe to rise
in the 2050s under RCP4.5 and RCP8.5 in the absence of significant
preventative measures. In a study of the combined effects of warming
temperatures and an aging population in Korea, Lee and Kim (2016)
projected a four- to six-fold increase in heat-related mortality by the
2090s when accounting for temperature and age structure.
7.1.7.3.4 Socioeconomically Marginalised Populations and People
with Disabilities
People living in poverty are more likely to be exposed to extreme
heat and air pollution and have poorer access to clean water and
sanitation, accentuating their exposure to climate change-associated
health risks (UNEP, 2021; FAO etal., 2018). Poverty influences how
people perceive the risks to which they are exposed, how they
respond to evacuation orders and other emergency warnings and
their ability to evacuate or relocate to a less risk-prone location (US
Global Change Research Program, 2016). Poorer households, who
often live in highly exposed locations, are more likely to be forced
into low-agency migration as a means of adapting to climate risks
and at the same time are the most likely to be immobile or trapped
in deteriorating circumstances where migration would be a preferred
response (Leichenko and Silva, 2014; Fazey etal., 2016; Sheller, 2018).
Climate emergencies disproportionally affect people with disabilities
because of their inherent vulnerabilities, which may impair their
ability to take protective action; they are also frequently excluded
from adaptation planning (Gaskin etal., 2017).
7.1.7.3.5 Urban Compared with Rural Populations
Rural and urban populations are often exposed to different types of
climate-related health risks. For example, because of the UHI effect
and high concentrations of air pollution from motor vehicles and
industrial activity, people who live in urban areas may have higher
rates of extreme heat stress and respiratory illnesses than their rural
counterparts (Hondula etal., 2014; Heaviside etal., 2016; Macintyre
et al., 2018; Schinasi et al., 2018). Conversely, rural populations,
especially those dependent on resource-based livelihoods, may have
a greater exposure to climate impacts on food production or natural
hazard events, which have subsequent effects on household nutrition
and food security (Springmann etal., 2016a; see also Chapters 5 and
6 of this report).
7.1.7.3.6 Indigenous Peoples
Indigenous Peoples, especially those who live in geographically
isolated, resource-dependent and/or impoverished communities, are
often at greater risk of health impacts of climate change (Ford etal.,
2020) (US Global Change Research Program, 2016). The close inter-
connection of land-based livelihoods and cultural identity of many
indigenous groups exposes them to multiple health- and nutrition-
related hazards (Durkalec et al., 2015; Sioui, 2019) with potential
implications for community social relations and individual mental
health (Cunsolo Willox et al., 2013; Cunsolo Willox et al., 2015).
Climate change risk exposures may be complicated by changes in
lifestyle, diet and morbidity driven by socioeconomic processes, further
increasing health risks for Indigenous Peoples (Jaakkola etal., 2018).
Environmental consequences of climate change can also affect social
ties and spiritual well-being, in part because land is often an integral
part of their culture and spiritual identity.
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Chapter 7 Health, Wellbeing and the Changing Structure of Communities
Box7.1 | Indigenous Peoples’ Health and Well-Being in a Changing Climate
Contributing authors: Hannah Tait Neufeld (Canada), Lena Maria Nilsson (Sweden), Rhys Griffith Jones (New Zealand)
The indigenous population worldwide is estimated at 476million people spread across all geographic regions of the world (FAO etal.,
2021). Indigenous Peoples globally represent a large heterogeneity of people in terms of living conditions and social determinants of
health. There is no simple definition of who is indigenous. In this text, we refer to Indigenous Peoples as people self-identified and
organised as indigenous, according to the principles of the International Work Group for Indigenous Affairs (IWGIA), an international non-
governmental organisation (NGO) with observer status at the United Nations (UN). Indigenous Peoples are described as ‘distinct social
and cultural groups that share collective ancestral ties to the lands and natural resources where they live, occupy or from which they have
been displaced’ (World Bank, 2021). A common experience among Indigenous Peoples are historical traumas related to overseas and/or
settler/industrial colonisation.
Studies on climate change as it affects the health of Indigenous Peoples generally focus on non-displaced indigenous groups; that
is, Indigenous Peoples maintaining culturally important elements of a land-based traditional lifestyle. Here we use an eco-medicine
perspective in which the impacts of climate change on health are divided into primary, secondary and tertiary effects, as discussed below
(Butler and Harley, 2010). Many analyses of indigenous health in relation to climate change use the One Health concept (Mackenzie and
Jeggo, 2019; see Section7.1.5).
Current Impacts of Climate Change on Health and Well-Being of Indigenous Peoples
Primary health effects of climate change include the immediate physical effects on human health, such as health hazards due to high
temperatures, extreme weather events or accidents from exposure to climate-related hazards. For example, in arid and semiarid areas,
an increased frequency of severe droughts is associated with immediate health problems related to overheating and lack of water for
drinking, sanitation and livestock (Hall and Crosby, 2020; Mamo, 2020; Rankoana, 2021). In many cases, the possibilities for Indigenous
Peoples to apply traditional strategies to mitigate droughts by migration are limited by competing land use, environmental protection
and national borders, with many examples across Africa (Mamo, 2020). In the Jordan River Valley, the second most water stressed area
in the world, water resources are not equally distributed to Indigenous Bedouin people, amplifying their immediate health threat during
predictable as well as unpredictable droughts (Mamo, 2020).
In Arctic and sub-Arctic areas, higher temperatures with increased numbers of freeze–thaw cycles during the winter means increased
occurrences of transport-related accidents in indigenous communities due to weaker ice on travel routes that cross lakes, rivers and the
sea, along with changes in the snow cover and increased risk of avalanches (Durkalec etal., 2015; Jaakkola etal., 2018). Impeded access
to healthcare during extreme weather conditions is a primary health risk for Indigenous Peoples living in remote areas (Amstislavski etal.,
2013; Hall and Crosby, 2020; Mamo, 2020).
Pastoralists in many regions may experience changes in livestock behaviour due to climate change, leading to increased mobility-related
health hazards (Jaakkola etal., 2018; Mamo, 2020). Indigenous Peoples living in low-lying coastal areas and small island states face long-
term risk of flooding and the stresses of resettlement (Maldonado etal., 2021; McMichael and Powell, 2021).
Extreme rainfall, flooding, storms, heatwaves and wildfires lead to individual health hazards that may include injuries and thermal and
respiratory traumas (Mamo, 2020) There are many examples when emergency responses to extreme events have ignored the needs
of displaced Indigenous Peoples (Mendez etal., 2020; Maldonado etal., 2021). Population-based quantitative studies documenting
the direct effects of these events on Indigenous Peoples are rare. In Mexico, respiratory diseases are almost twice as common among
Indigenous Peoples compared to non-Indigenous Peoples (de Leon-Martinez etal., 2020). In Alaska and northern Canada, alarming levels
of respiratory stress and disease have been reported among Inuit and First Nation communities in relation to wildfires (Howard etal.,
2021), as well as increased mould in houses due to flooding resulting from increased precipitation (Furgal and Seguin, 2006; Harper etal.,
2015; Norton-Smith etal., 2016). Climate- and housing-related respiratory stress is also a risk factor for severe COVID-19 infection, which
has been highlighted in recent literature from an indigenous health perspective (de Leon-Martinez etal., 2020).
Secondary effects relate to ecosystem changes, for example, the increased risk of the acute spread of air-, soil-, vector-, food-, and
waterborne infectious diseases (Hueffer etal., 2019). Higher proportions of climate-related infectious diseases are reported among
indigenous groups compared to their non-indigenous neighbours, with examples from Torres Strait, Australia, showing a greater proportion
of tuberculosis, dengue, Ross River virus, melioidosis, and non-tuberculous mycobacterial infections (Hall etal., 2021) and in the Republic
of Sakha, Russia, high levels of zoonoses (Huber etal., 2020a). Increasing levels of livestock and canine diseases are also reported (Mamo,
2020; Bogdanova etal., 2021; Hillier etal., 2021). Another secondary health effect is an increase in human–animal conflicts, for example
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Health, Wellbeing and the Changing Structure of Communities Chapter 7
human–elephant conflicts in Namibia due to plant food scarcity (Mamo, 2020), human–bear conflicts in Arctic regions within Canada
(Wilder etal., 2017), human–tiger conflicts in Bangladesh (Haque etal., 2015) and increased predatory pressure on Indigenous Peoples’
livestock and game worldwide (Haque etal., 2015; Jaakkola etal., 2018; Mukeka etal., 2019; Mamo, 2020; Terekhina etal., 2021).
Undernutrition and metabolic disturbances associated with overnutrition and obesity due to the decreased availability or safety of local
and traditional foods and increased dependency on imported substitutes affect many Indigenous Peoples worldwide (Amstislavski etal.,
2013; Zavaleta etal., 2018; Houde etal., 2020; Jones etal., 2020; Akande etal., 2021; Bogdanova etal., 2021; Bryson etal., 2021) and are
especially severe for pregnant women and small children (Mamo, 2020; Olson and Metz, 2020; Bryson etal., 2021); these are amplified
by the combination of warming and the COVID-19 situation (Zavaleta-Cortijo etal., 2020). Decreased access to wild plants and animals
as food sources and medicine due to climate change is another threat to the health and wellness of indigenous communities (Greenwood
and Lindsay, 2019; Mamo, 2020; CIAT and and, 2021; Rankoana, 2021; Teixidor-Toneu etal., 2021).
Tertiary effects relate to culture-wide changes, for example, all forms of malnutrition due to climate-driven changes in food systems
and anxiety, mental illness and suicidal thoughts related to cultural and spiritual losses. A wide range of tertiary, culture-related effects
of climate change have been documented for Indigenous Peoples. These include anxiety, distress and other mental health impacts due
to direct and indirect processes of dispossession of land and culture related to the combination of climate change and other factors
(Richmond and Ross, 2009; Bowles, 2015; Norton-Smith etal., 2016; Jaakkola etal., 2018; Fuentes etal., 2020; Mamo, 2020; Middleton
etal., 2020b; Middleton etal., 2020a; Olson and Metz, 2020; Timlin etal., 2021). Increased risks of conflict and abuse, including violence
and homicide against females, and/or conflicts resulting from environmental activism, are other tertiary health threats for Indigenous
Peoples (Mamo, 2020). Between 2017 and 2019, close to 500 indigenous people were killed for activism in 19 different countries (Mamo,
2020). In Uganda, climate change drives indigenous men to increase their distance and time from home and their families in search of
water and food, leading to an increase in sexual violence against indigenous women and girls in their communities (Mamo, 2020).
Gender inequities amplify the tertiary health effects of climate change (Williams, 2018; Garnier etal., 2020). In an Inuit community, for
instance, women reported a higher level of mental stress related to climate change than men (Harper etal., 2015). Adverse pregnancy
outcomes and altered developmental trajectories have also been associated with climate change (Hall etal., 2021). Indigenous Batwa
women in Uganda reported experiencing more severe circumstances of food insecurity during pregnancy due to drought and unpredictable
seasons negatively impacting agricultural practices (de Leon-Martinez etal., 2020). More studies with a gender perspective on climate
change as a determinant of Indigenous Peoples’ health are needed, along with the perspectives of indigenous children and youth,
displaced individuals and communities in urban settings (Kowalczewski and Klein, 2018).
Because cultural continuity is a recognised health factor (Lemelin etal., 2010; de Leon-Martinez etal., 2020; Middleton etal., 2020b),
displaced Indigenous Peoples may suffer from climate change by worrying about impacts on non-displaced relatives and family and
from traditional food staples turning into expensive commodified products. This is a knowledge gap with lasting implications not only
on physical environments (Guo etal., 2018). Social connections and knowledge pathways are disrupted, leading to a decreased ability to
share locally harvested and cultivated foods (King and Furgal, 2014; Neufeld etal., 2020).
Tertiary effects of climate change on Indigenous Peoples’ health are primarily described in smaller case studies and not designed in a
way allowing for systematic international comparisons, which represents an important and significant gap in our understanding of these
often-complex associations and impacts (Middleton etal., 2020b).
Future Risks for Indigenous People’s Health and Well-Being in a Changing Climate
Future risks for Indigenous Peoples’ health and well-being in a changing climate will result foremost from exacerbations of observed
impacts. Primary and secondary health risks are expected to increase as the frequency and/or severity of climate hazards grow in many
regions. As one example, melting permafrost in the Siberian Arctic is projected to lead to more outbreaks of anthrax (Bogdanova etal.,
2021). Tertiary health threats are expected to persist even with strong global initiatives to mitigate greenhouse gases (GHGs) (Butler and
Harley, 2010). Climate change is expected to compound non-climatic processes that lead to social exclusion and land dispossession that
underlay health inequalities experienced by Indigenous Peoples (Huber etal., 2020a).
Options and Opportunities for Reducing Future Risks and Building Capacity/Resilience for Indigenous Peoples’ Health and
Well-Being
Indigenous organisations worldwide stress the importance of applying a rights-based approach in responding to climate change (Mamo,
2020). Although Indigenous Peoples are often identified as being vulnerable to climate change, this framing does not always reflect the
diverse responses and adaptations of Indigenous Peoples to these ongoing challenges (Nursey-Bray etal., 2020). An emerging body of
Box7.1 (continued)
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Chapter 7 Health, Wellbeing and the Changing Structure of Communities
research is focusing on the strength and resilience of indigenous communities globally as they adapt to these complex changes (Whyte,
2018; FAO etal., 2021).
During droughts and water shortages, for example, indigenous pastoralists may face additional challenges if water supply assistance
provides only for human needs and neglects water requirements of livestock (Mamo, 2020). Indigenous knowledge on how to adapt to
drought through storing and sharing strategies, for example, is valuable (Fatehpanah etal., 2020; Mamo, 2020).
Indigenous Peoples have been adapting to changes in their environments since time immemorial by developing new practices and
techniques (FAO et al, 2021). Their beliefs, value systems and principles include core elements and common values such as reciprocity,
solidarity, co-responsibility and community that are expressed in the dynamism of their knowledge systems (Lewis etal., 2020; Schramm
etal., 2020b). The relevance of these knowledge systems, which are holistic and tied to relationships between all living things, cannot be
ignored at this critical time (Garnier etal., 2020).
The health and equity impacts of climate change for Indigenous Peoples make mitigation efforts critical (Jones etal., 2020), including
policies and actions that consider the effects of colonisation. Colonisation constrains the design and diversity of potential climate
and health responses through its historic and ongoing suppression of Indigenous knowledge systems that are critical in supporting
community-led actions to reduce future risks (Billiot etal., 2019; Reid etal., 2019; Nursey-Bray etal., 2020).
Four Brief Case Studies to Illustrate the Innovativeness of Indigenous Peoples’ Adaptation to Climate Risks
Bedouin Pastoralists’ Grazing Practices Decrease the Risk of Wildfires in Israel and Increase Food Sovereignty
Wildfires are a main cause of deforestation in Israel, and in recent years climate stress has decreased the forest resilience to fires (Klein
etal., 2019). The original landscape, a shrubland or maquis consisting mostly of oak and Pistacia, has been used since time immemorial
as grazing land for goats, sheep and camels belonging to Indigenous Bedouin people (Degen and El-Meccawi, 2009). Competing land use
has reshaped the landscape with pine monocultures and cattle farming, reducing the availability of land suitable for herding goats the
indigenous way (Perevolotsky and Sheffer, 2011). In addition, since 1950, plant protection legislation has decreased Bedouin forest
pastoralism in Israel by defining indigenous black goats as an environmental threat (FAOLEX, 2021). In nature reserves where no human
interference has been allowed, these areas have regenerated into herbaceous shrublands susceptible to wildfires (Turco etal., 2017).
Meanwhile, urbanised Bedouin exist on lower incomes and experience higher levels of unemployment compared to other citizens, and
some keep non-pastoralised livestock in cities as a strategy for food sovereignty (Degen and El-Meccawi, 2009). In 2019, many severe
wildfires occurred in Israel due to extreme heatwaves and, in response, plant protection legislation was repealed, allowing Bedouin
pastoralists to graze their goats in areas from which they had been excluded. The amount of combustible undergrowth subsequently
decreased, reducing the risk for wildfire and their related impacts, while simultaneously facilitating indigenous food sovereignty among
the Bedouin (Mamo, 2020).
Gardening in the Ashes of Wildfires in the Pacific Northwest as a Strategy to Decrease Food Insecurity and Increase Connections With the Land
In the central interior of what is now known as British Columbia (BC), 2017 was an especially severe wildfire season, with over 1.3million
hectares of land burned and 65,000 people displaced (Timler and Sandy, 2020). The unceded and ancestral lands of the Tsilhqot’in,
Dakelh and Secwépemc were impacted by two of the largest fires (Verhaeghe etal., 2017). Communities affected by the BC wildfires
subsequently started indigenous gardens closer to home, to protect medicine and food plants and thereby sustaining relationships with
these plants, the land and the community (Timler and Sandy, 2020). As there are cultural teachings for fire to cleanse the territory and
the land, community members and plants previously isolated became better connected because of the wildfires. The regrowth of plants is
part of the healing relationship between plants, people and other animals (Timler and Sandy, 2020). The wildfires were seen as events to
catalyse action and emphasise the importance of relationships to support foodways and gardening as responsibility.
Widening our understanding of gardening in the face of climate change and colonialism can support health and healing for Indigenous
and non-Indigenous Peoples. Gardening as a means of indigenous food sovereignty has long been utilised by a variety of indigenous
groups within Canada and elsewhere to address circumstances of chronic food insecurity and support health and wellness (Johnson-
Jennings etal., 2020; Timler and Sandy, 2020). The concept of gardening as both a Euro-Western agricultural practice and indigenous
practice encourages an increased reverence and connection with the land and wider engagement with the natural world (Whyte, 2018).
Much of this is because Indigenous knowledge and land management practices encompass processes that are known to be synergistic
Box7.1 (continued)
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Health, Wellbeing and the Changing Structure of Communities Chapter 7
and sustainable (Ottenhoff, 2021). Indigenous worldviews offer a different perspective on social resilience to environmental change, one
that is based on moral relationships of responsibility that connect humans to animals, plants and habitats (Grey and Patel, 2015). These
responsible practices not only ensure ecosystems are maintained for future generations; they centre the moral qualities necessary to carry
out the responsibilities of consent, reciprocity and trust. Moral qualities of responsibility are the foundation for relying on each other
when facing environmental challenges (Whyte, 2018; Miltenburg etal., 2021).
To restore these sustainable relationships, a resurgence is needed of community roles and responsibilities (Cidro etal., 2015) as well as
a reconsideration of the concept of food security and the role of gardening within diverse indigenous contexts. Offering individual or
community gardening as a solution to ‘food insecurity’, a Eurocentric measure of health, ignores colonial contexts and sovereignty
(Borrows, 2019; Timler and Sandy, 2020). Indigenous communities have historic, ongoing and evolving gardening and food gathering
practices, including a wide variety of land-based and aquatic foods (Turner and Turner, 2008; Mt. Pleasant, 2016). Euro-Western science
is beginning to recognise these longstanding relationships (Kamal etal., 2015; Hatfield etal., 2018; Timler and Sandy, 2020). For many
indigenous communities, reconnecting with ancestral foodways holds the potential not only to address food security but to provide the
community cohesion, self-esteem and wellness (Gordon etal., 2018).
A New Food Composition Database in Uganda to Guide Local Policy in Healthy Eating Based on Indigenous Foods
In sub-Saharan Africa, climate change is an emerging risk factor for undernutrition, particularly in countries that rely on subsistence
agriculture (Sorgho etal., 2020). In Uganda, negative health effects associated with climate change are being observed, including
increased rates of food insecurity, with the highest rates recorded among the Batwa of Kanungu District, where 97% of households are
severely food insecure (Patterson etal., 2017). For many Indigenous Peoples, food security in a changing climate is a growing concern
(Guyot etal., 2006; Patterson etal., 2017). Locally harvested indigenous foods have been adversely impacted by climate change, while
connection to land is being disrupted by the processes of colonisation, discrimination and lack of representation in decision-making
groups, thereby restricting adaptive capacity for indigenous communities (Bryson etal., 2021). In Uganda, the Indigenous Batwa have
experienced significant disparities resulting from the forced eviction from their territory, dispossessing them of their land and the ability
to provide indigenous foods to their families (Patterson etal., 2017; Scarpa etal., 2021).
Nutrient-specific knowledge of indigenous foods is limited among many communities in Africa. A new food composition database in
Uganda was constructed in dialogue with knowledge keepers from the Batwa and Bakiga Peoples to assess the nutrient density of these
locally harvested foods (Scarpa etal., 2021). As in other lower resource settings, no food composition tables are available for southwestern
Uganda. The only existing food database was designed for central and eastern Uganda; it does not include common recipes and local
foods consumed by Batwa and Bakiga communities (Scarpa etal., 2021). Using a community-based approach and collaboration with
local nutritionists, a list of foods was collected through focus group discussions, an individual dietary survey and market assessments.
Including these locally familiar foods ultimately supports a focus on indigenous justice and the importance of valuing indigenous food
systems and practices, which in many contexts have been found to have superior nutritional and environmental benefits for communities
(Kuhnlein etal., 2013; Scarpa etal., 2021). This new and unique database including indigenous foods will not only guide local nutrition
and health initiatives, but also contribute towards policies related to indigenous food sovereignty and resilience to climate change.
Decreased Fragmentation of Winter Grazing Increases Mental and Spiritual Well-Being in Reindeer Herding Sámi and Decreases their
Dependency on Fossil Fuels
Sami are the Indigenous Peoples of northernmost Scandinavia and the Kola Peninsula of Russia, whose livelihoods have been traditionally
sustained by reindeer herding, hunting, fishing and small-scale farming (Nilsson etal., 2011). Climate change is threatening core conditions
for reindeer herding, with Sami pastoralists describing the situation as ‘facing the limit of resilience’ (Furberg etal., 2011). Sami pastoralists
stress that an ability to continue reindeer herding is a prerequisite for their mental and spiritual health (Jaakkola etal., 2018).
In a pilot project for climate adaptation of reindeer herding run by the Swedish Sami Parliament, reindeer herding management plans (in
Swedish, renbruksplaner) were used as a tool to develop strategies for climate adaptation (Walkepää, 2019). Four Sami reindeer herding
cooperatives participated in the pilot study. They all agreed that climate change means that grazing patterns need to change. Traditionally,
mountain reindeer graze in the Scandinavian mountains close to Norway in summer and in the coastal areas close to the Gulf of Bothnia
in winter, representing a total migration route of up to 400 kilometres one-way. Rising temperatures are causing spring to occur earlier
in the coastal winter grazing land before the calving areas in the summer land are suitable for grazing and free from snow. When the
snow cover disappears, the herds are dispersed, so it is important to migrate while snow is still present (Walkepää, 2019). Migration
Box7.1 (continued)
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Chapter 7 Health, Wellbeing and the Changing Structure of Communities
routes are being destabilised by weaker ice cover on water and by hazardous weather events. Competing land use due to infrastructure,
extractive industries, tourism, and energy production makes it difficult to find alternative grazing land. Supplementary feeding and
increased use of trucks to transport reindeer is one result. Herds that are dispersed due to bad snow conditions have an increased
exposure to predators (Walkepää, 2019; Uboni etal., 2020). By working strategically to secure adequate winter grazing and reduce
fragmentation of grazing areas more generally represents win-win strategies for achieving decreased mental stress levels while reducing
herders’ consumption of fossil fuels (Walkepää, 2019).
Box7.1 (continued)
7.1.7.3.7 Vulnerability Experienced through Food Systems
Stresses and shocks associated with climate change are drivers of food
insecurity, particularly in sub-Saharan Africa, Asia and Latin America
(Betts etal., 2018). The most vulnerable groups include smallholder
farmers, pastoralists, agricultural laborers, poorer households, refugees,
indigenous groups, women, children, the elderly and those who are
socioeconomically marginalised (FAO etal., 2018; IPCC, 2019b) (high
confidence). Men, women, children, the elderly and the chronically
ill have different nutritional needs and these vulnerabilities may be
amplified by gendered norms and differential access to resources,
information and power (IPCC, 2019b). Extreme climate events have
immediate and long-term impacts on food insecurity and malnutrition
in poor and vulnerable communities, including when women and girls
need to undertake additional duties as laborers and caregivers (FAO
etal., 2018).
7.1.7.3.8 Health Vulnerability Experienced through Water and
Sanitation Systems
Water and sanitation systems are particularly vulnerable to extreme
weather events, and damage to such systems can lead to contamination
of drinking water and subsequent adverse health impacts (Howard
etal., 2016; Khan etal., 2015; Sherpa etal., 2014). In areas with only
very simple traditional excreta disposal facilities (e.g., latrines) and
traditional sources of water (e.g., unprotected wells), the repeated
Structure of chapter 07
Section 7.2Section 7.3
ADAPTATION &
CLIMATE RESILIENT
DEVELOPMENT PATHWAYS
(CRDP)
Health sector
Other sectors
Governance
OBSERVED IMPACTS

Health

Wellbeing

Migration

Conflict
PROJECTED
FUTURE RISKS
Section 7.4
Hazard
Section 7.1
FUTURE EMISSIONS
(RCPs)
2.6
4.5
6
8.5
Challenges for adaptation
FUTURE SOCIO-ECONOMIC
& DEMOGRAPHIC PATHWAYS
(SSPs)
SSP1
SSP3
SSP2
SSP4
SSP5
Challenges for mitigation
+
Vulnerability
Exposure
Hazard
Risk
Figure7.3 | Structure of the chapter following a pathway from hazard, exposure and vulnerability to the observed impacts, projected future risks, adaptation
and climate resilient development pathways.
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Health, Wellbeing and the Changing Structure of Communities Chapter 7
occurrence of floods and other extreme events can negatively affect
water quality at household and community levels and increase the
burden of food- and waterborne diseases (Cissé etal., 2016; Khan
etal., 2015; Kostyla etal., 2015).
7.1.8 Visual Guide to this Chapter
Figure7.3 provides a visual guide to this chapter. Section7.1 has briefly
summarised major global frameworks and highlights groups that exhibit
heightened vulnerability and exposure to the climatic risks assessed in
this chapter. Section7.2 assesses observed impacts on health and well-
being, migration and conflicts that have emerged from interactions of
climate and weather-related hazards, exposure to such hazards and
vulnerability of communities and systems, while Section7.3 assesses
projected future risks. Section 7.4 assesses adaptation responses to
climate risks, opportunities for transformative change, co-benefits
and how solutions for reducing climate impacts on health, well-being,
migration and conflicts may form part of the wider CRDPs.
7.2. Observed Impacts of Climate Change on
Health, Well-Being, Migration and Conflict
7.2.1 Observed Impacts on Health and Well-Being
Eleven categories of diseases and health outcomes have been identified
in this assessment as being climate-sensitive through direct pathways
(e.g., heat and floods) and indirect pathways mediated through natural
and human systems and economic and social disruptions (e.g., disease
vectors, allergens, air and water pollution, and food system disruption)
(high confidence). A key challenge in quantifying the specific
relationship between climate and health outcomes is distinguishing
the extent to which observed changes in prevalence of a climate-
sensitive disease or condition are attributable directly or indirectly to
climatic factors as opposed to other non-climatic causal factors (Ebi
etal., 2020). A subsequent challenge is then determining the extent
to which those observed changes in health outcomes associated
with climate are attributable to events or conditions associated with
natural climate variability compared to persistent human induced
shifts in the mean and/or the variability characteristics of climate
(i.e., anthropogenic climate change). The context within which the
impacts of climate change affect health outcomes and health systems
is described in this chapter as being a function of risk, which is in turn
a product of interactions between hazard, exposure and vulnerability
(Chapter 1), with the impacts in turn having the potential to reinforce
vulnerability and/or exposure to risk (Figure7.4).
Interactions between hazard, exposure and vulnerability
Vulnerability
Exposure
Hazard
Risk
Age
Gender
Mobility
Access to care
Socio-economic status
Pre-existing conditions
Characteristics of health system
Outdoor employment
Housing quality
Location/local geography
Livelihood type
Heat, drought
Floods
Storms
Vector spread
CLIMATE SENSITIVE OUTCOMES
- Adverse health (VBD, WBD, FBD, infectious disease,
heat-related illness, mental health, under nutrition)
- Migration & displacement
- Conflicts
SYSTEM IMPACTS
Health system (patient loads, emergency responses, costs)
- Food systems
- Livelihood systems
IMPACTS
Figure7.4 | Interactions between hazard, exposure and vulnerability that generate impacts on health systems and outcomes, with selected examples.
WBD: waterborne disease, VBD: Vector-borne disease, and FBD: Food-borne disease.
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Chapter 7 Health, Wellbeing and the Changing Structure of Communities
Box7.2 | The Global Burden of Climate-Sensitive Health Outcomes Assessed in this Chapter
Global statistics for death and loss of health are increasingly described in terms of burden, which describes gaps between a population’s
actual health status and what its status would be if its members lived free of disease and disability to their collective life expectancy
(Shaffer etal., 2019). Burden for each disease/health outcome is estimated by adding together the number of years of life lost (YLL) by
a person because of early death and the number of years of life lived with disability (YLD) from the considered outcome. The resulting
statistic, the disability-adjusted life year (DALY) represents the loss of one year of life lived in full health. The total global burden of
disease (Vos etal., 2020), expressed in DALYs, is what the world’s health systems must manage and is reported annually in Global Burden
of Disease Study (Vos etal., 2020). The estimated current global burden of climate-sensitive diseases and conditions described in this
chapter, and the geographical regions most affected, are summarised in Table Box7.2.1. As was observed in Chapter 11 (‘Human Health’)
of AR5, the ‘background climate-related disease burden of a population is often the best single indicator of vulnerability to climate
change – doubling of risk of disease in a low disease population has much less absolute impact than doubling of the disease when the
background rate is high.
The global magnitude of climate-sensitive diseases was estimated in 2019 to be 39,503,684 deaths (69.9% of total annual deaths) and
1,530,630,442 DALYs (Vos etal., 2020). Of these, cardiovascular diseases (CVDs) comprised the largest proportion of climate-sensitive
diseases (32.8% of deaths and 15.5% DALYs). The next largest category consists of respiratory diseases – with chronic respiratory disease
contributing to 7% of deaths and 4.1% of DALYs and respiratory infection and tuberculosis contributing to 6.5% of deaths and 6% of
DALYs. The observed trend of climate-sensitive disease deaths since 1990 is marked by increasing cardiovascular mortality and decreasing
mortality from respiratory infections, enteric diseases and other infectious diseases (Vos etal., 2020). Figure Box7.2.1 illustrates specific
global trends between 1990 and 2017 of selected health outcomes estimated by GBDs (Ahmad Kiadaliri etal. 2018).
TableBox7.2.1 |Global burden of climate-sensitive health risks assessed in this chapter (in order of assessment) (Vos etal., 2020) and synthesis of major observed
and projected impacts in most affected regions. Blue represents an increase in positive health impacts, green represents an increase in negative health impacts and yellow
represents an increase in both positive and negative impacts, but not necessarily in equal proportions. The confidence level refers to both the attributed observed and
projected changes to climate change. No assessment means the evidence is insufficient for assessment.
Data from Global Burden of Disease 2019
(Vos etal. 2020)
Chapter 7 Assessment
Health outcome (disease/
condition)
Global annual deaths
Regions most
affected (deaths)
Climate change observed
impacts
Climate change
projected impacts in
most affected regions
Selected key
references of the
Assessment
Malaria 643,381 Africa (92%) **** ***
M’Bra etal. (2018);
Caminade etal. (2019);
Gibb etal. (2020);
Tompkins and Caporaso
(2016b); Ebi etal.
(2021a)
Dengue 36,055 Asia (96%) *** ***
Bhatt etal. (2013);
Rocklöv & Dubrow
(2020); Messina etal.
(2019); Monaghan etal.
(2018)
Diarrhoeal diseases 1,534,443 Asia (56%) *** **
Cissé (2019); Levy etal.
(2018); Lo Iacono etal.
(2017); Carlton etal.
(2016)
Salmonella 79,046 Africa (89%) *** **
Cissé (2019); Smith and
Fazil (2019); Lake (2017)
RTIs 2,493,200 Asia (47%) **
Geier etal. (2018);
Oluwole (2017)
Non-communicable
respiratory illness
3,741,705 Asia (74%) *** **
Schweitzer etal. (2018);
Hansel etal. (2016);
Collaco etal. (2018);
D’Amato etal. (2020);
Silva etal. (2017);
Doherty etal. (2017);
Beggs (2021)
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Health, Wellbeing and the Changing Structure of Communities Chapter 7
Data from Global Burden of Disease 2019
(Vos etal. 2020)
Chapter 7 Assessment
CVD 18,562,510 Asia (58%) ** ***
Stewart etal. (2017);
Phung (2016); Sun
(2018); Wang (2016);
Tian (2019); Chen (2019);
Zhang (2018)
Death from malignant
neoplasms
10,079,637 Asia (55%) ***
Ahmed etal. (2014);
Modenese etal. (2018);
Prueksapanich etal.
(2018)
Diabetes 1,551,170 Asia (56%) ** **
Hajat etal. (2017); Xu
etal. (2019b); Li etal.
(2014);Yang etal. (2016);
Velez-Valle etal. (2016);
Quast and Feng (2019)
Environmental heat and
cold exposure
47,461 Asia (46%) *** ****
Zhang etal. (2019b);
Green etal. (2019);
Murray etal. (2020); Ma
and Yuan (2021); Jones
etal. (2018); Russo etal.
(2019); Gosling etal.
(2017)
Nutritional deficiencies 251,577 Africa (43%) *** ***
Mbow etal. (2019); Lloyd
(2018); Springmann
etal. (2016b); Zhu etal.
(2018); Weyant etal.
(2018)
Mental healtha n.a. n.a. **** ****
Cianconi etal. (2020);
Charlson etal. (2021);
Hayes and Poland
(2018); Hrabok etal.
(2020); Obradovich etal.
(2018)
Legend
Climate change impacts Confidence
Positive health impacts Very high ****
Negative health impacts High ***
Positive and negative impacts Medium **
No assessment Low *
Notes:
(a) Mental health data were not available (n.a.) due to lack of information in GBD 2019 related to annual deaths and the most affected regions.
Box7.2 (contnued)
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Chapter 7 Health, Wellbeing and the Changing Structure of Communities
Global trends of selected health outcomes estimated by the Global Burden of Disease Study
2.0
100
50
0
1990 1999 2008 2017
150
100
50
0
Diarrhoeal disease
Malaria
40
30
20
0
10
1990 1999 2008 2017
10
5
0
Forces of nature
Protein-energy malnutrition
1990 1999 2008 2017
10
5
0
2.0
1.5
1.0
0.1
0
Dengue
Heat and cold exposure
Deaths per 100,000 people Deaths per 100,000 people
All causes
1400
1200
1000
800
600
0
1990 1999 2008 2017
African region
Region of the Americas
Eastern Mediterranean region
European region
South-East Asia region
Western Pacific region
FigureBox7.2.1 | Global trends of selected health outcomes estimated by GBDs. Source: Ahmad Kiadaliri etal. (2018a).
Box7.2 (contnued)
7.2.2 Observed Impacts on Communicable Diseases
7.2.2.1 Observed Impacts on Vector-Borne Diseases
Climate-sensitive VBDs include mosquito-borne diseases, rodent-borne
diseases and tick-borne diseases. Many infectious agents, vectors, non-
human reservoir hosts, and pathogen replication rates can be sensitive to
ambient climatic conditions. Elevated proliferation and reproduction rates
at higher temperatures, longer transmission season, changes in ecology
and climate-related migration of vectors, reservoir hosts or human
populations contribute to this climate sensitivity (Rocklöv & Dubrow,
2020; Semenza and Paz, 2021). Age-standardised DALY rates for many
VBDs have decreased over the last decade due to factors unrelated to
climate. Vulnerability to VBD is strongly determined by sociodemographic
factors (e.g., children, the elderly and pregnant women are at greater
risk) with exposure to vectors being strongly influenced by various
factors including socioeconomic status, housing quality, healthcare
access, susceptibility, occupational setting, recreational activity, conflicts
and displacement ( Rocklöv & Dubrow, 2020; Semenza and Paz, 2021).
Figure7.5 illustrates how climatic and non-climatic drivers and responses
determine VBD outcomes.
Evidence has increased since AR5 that the vectorial capacity has
increased for dengue fever, malaria and other mosquito-borne
diseases and that higher global average temperatures are making
wider geographic areas more suitable for transmission (very high
confidence). Transmission rates of malaria are directly influenced by
climatic and weather variables such as temperature, with non-climatic
socioeconomic factors and health system responses counteracting
the climatic drivers (very high confidence). The burden of malaria is
greatest in Africa, where more than 90% of all malaria-related deaths
occur (M’Bra etal., 2018; Caminade etal., 2019). Between 2007 and
2017, DALYs for malaria have decreased by 39% globally. Malaria
is mainly caused by five distinct species of plasmodium parasite
(Plasmodium falciparum, Plasmodium vivax, Plasmodium malariae,
Plasmodium ovale and Plasmodium knowlesi) and is transmitted by
Anopheline mosquitoes. Evidence suggests that in highland areas of
Colombia and Ethiopia, malaria has shifted in warmer years towards
higher altitudes, indicating that, without intervention, malaria will
increase at higher elevations as the climate warms (Siraj etal., 2014;
Midekisa etal., 2015). Each year, local outbreaks of malaria occur due
to importation in areas from which it was once eradicated, such as
Europe, but the risk of re-establishment is considered low.
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Health, Wellbeing and the Changing Structure of Communities Chapter 7
The transmission of dengue fever is linked to climatic and weather
variables such as temperature, relative humidity and rainfall (high
confidence). The dengue virus is carried and spread by Aedes
mosquitoes, primarily Aedes aegypti. Dengue has the second highest
burden of VBDs, with the majority of deaths occurring in Asia (Bhatt
et al., 2013). Since 1950, global dengue burden has grown and is
attributable to a combination of climate-associated expansion in the
geographic range of the vector species and non-climatic factors such
as globalised air traffic, urbanisation and ineffective vector abatement
measures. Temperature, relative humidity and rainfall variables are
significantly and positively associated with increased dengue case
incidence and/or transmission rates globally, including in Vietnam
(Phung etal., 2015; Xuan le etal., 2014), Thailand (Xu etal., 2019a),
India (Mutheneni etal., 2017; Rao etal., 2018; Mala and Jat, 2019),
Indonesia (Kesetyaningsih etal., 2018), the Philippines (Carvajal etal.,
2018), the USA (Lopez etal., 2018; Pena-Garcia etal., 2017; Duarte
etal., 2019; Rivas etal., 2018; Silva etal., 2016a), Jordan (Obaidat
and Roess, 2018) and Timor-Leste (Wangdi etal., 2018). Variation in
winds, sea surface temperatures and rain over the tropical eastern
Pacific Ocean (El Niño-Southern Oscillation; ENSO) have been linked to
increased dengue incidence in Colombia (Quintero-Herrera etal., 2015;
McGregor and Ebi, 2018; Pramanik etal., 2020) and its interannual
variation successfully forecasted in Ecuador using ENSO indices
as predictors (Petrova etal., 2019). The observed time lag between
climate exposures and increased dengue incidence is approximately
1–2months (Chuang etal., 2017; Lai, 2018; Chang etal., 2018).
Changing climatic patterns are facilitating the spread of CHIKV, Zika,
Japanese encephalitis and Rift Valley Fever in Asia, Latin America,
North America and Europe (high confidence). Climate change may
have facilitated the emergence of CHIKV as a significant public health
challenge in some Latin American and Caribbean countries (Yactayo etal.,
2016; Pineda etal., 2016) and contributed to chikungunya outbreaks
in Europe (Rocklöv etal., 2019; Mascarenhas etal., 2018; Morens and
Fauci, 2014). The Zika virus outbreak in South America in 2016 was
preceded by 2007 outbreaks on Pacific islands and followed a period
of record high temperatures and severe drought conditions in 2015
(Paz and Semenza, 2016; Tesla etal., 2018). Increased use of household
water storage containers during the drought is correlated with a range
expansion of Aedes aegypti during this period, increasing household
exposure to the vector (Paz and Semenza, 2016). Changing climate also
appears to be a risk factor for the spread of Japanese encephalitis to
higher altitudes in Nepal (Ghimire and Dhakal, 2015) and in southwest
China (Zhao etal., 2014). In eastern Africa, climate change may be a risk
factor in the spread of Rift Valley Fever (Taylor etal., 2016a).
Changes in temperature, precipitation, and relative humidity have
been implicated as drivers of West Nile fever in southeastern Europe
(medium confidence). The average temperature and precipitation prior
to the exceptional 2018 West Nile outbreak in Europe was above the
1981–2010 period average, which may have contributed to an early
upsurge of the vector population (Marini etal., 2020; Haussig etal.,
2018; Semenza and Paz, 2021). In 2019 and 2020, West Nile fever was
first detected in birds and subsequently in humans in Germany and the
Netherlands (Ziegler etal., 2020; Vlaskamp etal., 2020).
Climate change has contributed to the spread of the Lyme disease
vector Ixodes scapularis, a corresponding increase in cases of Lyme
disease in North America (high confidence) and the spread of the Lyme
disease and tick-borne encephalitis vector Ixodes ricinus in Europe
Analysis of the
underlying drivers of
infectious disease threat
events (IDTE)
detected in Europe during
2008–2013 by epidemic
intelligence at the European
Centre of Disease Prevention
and Control
Surveillance and
reporting failure
Occupational Prevention LifestyleMigration
Travel and
tourism
Global trade
Natural
environment
Human-made
environmentClimate
IDTE (epidemics or first
autochthonous cases) of
vector-borne diseases
Globalization and
environmental drivers
Public health systems drivers
Sociodemographic drivers
Size is proportional to the overall
requency of the driver
Figure7.5 | Analysis of the underlying drivers of infectious disease threat events (IDTEs) detected in Europe from 2008 to 2013 by epidemic intelligence
at the European Centre of Disease Prevention and Control. Seventeen drivers were identified and categorised into three groups: globalisation and environment (green),
sociodemographic (red) and public health system (blue). The drivers are illustrated as diamond shapes and arranged in the top and bottom row; the sizes are proportional to the
overall frequency of the driver. Here IDTEs (epidemics or first autochthonous cases) of VBDs are illustrated as a horizontal row of dots in the middle. These empirical data include
the IDTEs of VBDs such as West Nile fever, malaria, dengue fever, chikungunya and Hantavirus infection. Source: Semenza etal. (2016).
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Chapter 7 Health, Wellbeing and the Changing Structure of Communities
(medium confidence). In Canada, there has been a geographic range
expansion of the black-legged tick I. scapularis, the main vector of
Borrelia burgdorferi, the agent of Lyme disease. Vector surveillance of I.
scapularis has identified strong correlation between temperatures and
the emergence of tick populations, their range and recent geographic
spread, with recent climate warming coinciding with a rapid increase
in human Lyme disease cases (Clow etal., 2017; Cheng etal., 2017;
Gasmi etal., 2017; Ebi etal., 2017). Ixodes ricinus, the primary vector
in Europe for both Lyme borreliosis and tick-borne encephalitis is
sensitive to humidity and temperature (Daniel etal., 2018; Estrada-
Peña and Fernández-Ruiz, 2020) (high confidence). There has been an
observed range expansion to higher latitudes in Sweden and to higher
elevations in Austria and the Czech Republic.
Rodent-borne disease outbreaks have been linked to weather and
climate conditions in a small number of studies published since AR5,
but more research is needed in this area. In Kenya, a positive association
exists between precipitation patterns and Theileria-infected rodents,
but for Anaplasma, Theileria and Hepatozoon, the association between
rainfall and pathogen varies according to rural land use types (Young
etal., 2017). Weather variability plays a significant role in transmission
rates of haemorrhagic fever with renal syndrome (HFRS) (Hansen etal.,
2015; Xiang etal., 2018; Liang etal., 2018; Fei etal., 2015; Xiao etal.,
2014; Vratnica etal., 2017; Roda Gracia etal., 2015; Monchatre-Leroy
etal., 2017; Bai etal., 2019). In Chongqing, HFRS incidence has been
positively associated with rodent density and rainfall (Bai etal., 2015).
7.2.2.2 Observed Impacts on Waterborne Diseases
Important waterborne diseases (WBDs) include diarrhoeal
diseases (such as cholera, shigella, cryptosporidiosis and typhoid),
schistosomiasis, leptospirosis, hepatitis A and E and poliomyelitis (Cisse,
2019; Houéménou etal., 2021; Hassan etal., 2021; Archer etal., 2020;
Mbereko etal., 2020; Fan etal., 2021). The number of cases of WBDs
is considerable, and even in high-income countries WBDs continue
to be a concern (Cissé etal., 2018; Kirtman etal., 2014; Levy etal.,
2018; Murphy etal., 2014; Brubacher etal., 2020; Lee etal., 2021).
Nevertheless, diarrhoea mortality has declined substantially since
1990, although there are variations by country, and the global burden
of WBDs has decreased in line with vaccination coverage of some
WBDs (such as polio and cholera), poverty reduction and improved
sanitation and hygiene (Jacob and Kazaura, 2021; Mutono etal., 2020;
Lee etal., 2019; Semenza and Paz, 2021; Jacob and Kazaura, 2021;
Mutono etal., 2020).
Drinking water containing pathogenic microorganisms is the main
driver of the burden of WBDs (Murphy etal., 2014; Lee etal., 2021;
Chen etal., 2021b; Musacchio etal., 2021). WBD outbreaks, particularly
intestinal diseases, are attributable to a combination of the presence
of particular pathogens (bacteria, protozoa, viruses or parasites) and
the characteristics of drinking water systems in a given location (Bless
etal., 2016; Ligon and Bartram, 2016; Mutono etal., 2021; Ferreira
etal., 2021).
Since AR5 there is a growing body of evidence that increases in
temperature (very high confidence), heavy rainfall (high confidence),
flooding (medium confidence) and drought (low confidence) are
associated with an increase of diarrhoeal diseases. In the majority of
studies there is a significant positive association observed between
WBDs and elevated temperatures, especially in areas where water,
sanitation and hygiene (WASH) deficiencies are significant (Levy
etal., 2018; Carlton etal., 2016; Levy etal., 2018; Sherpa etal., 2014;
Guzman Herrador etal., 2015; Levy etal., 2016; Lo Iacono etal., 2017).
In Ethiopia, South Africa and Senegal, increases in temperatures are
associated with increases in diarrhoea, while in Ethiopia, Senegal and
Mozambique, increases in monthly rainfall are associated with an
increase in cases of childhood diarrhoea (Azage etal., 2015; Thiam
etal., 2017; Horn etal., 2018). Similar associations between weather
and diarrhoea have been observed in Cambodia, China, Bangladesh,
Pacific Island countries and the Philippines (McIver et al., 2016a;
McIver etal., 2016b; Liu etal., 2018; Wu etal., 2014; Matsushita etal.,
2018). Heavy precipitation events have been consistently associated
with outbreaks of WBDs in Europe, USA, UK and Canada (Guzman
Herrador etal., 2015; Levy etal., 2016; Lo Iacono etal., 2017; Curriero
etal., 2001; Guzman Herrador etal., 2016; Levy etal., 2018; Semenza
and Paz, 2021).
Impacts of floods include outbreaks of WBDs, with such events
disproportionately affecting the young, elderly and immunocompromised
(Suk etal., 2020; Guzman Herrador etal., 2015; Levy etal., 2016; Lo
Iacono etal., 2017; Zhang etal., 2019a). Water shortage and drought
have been found associated with diarrhoeal disease peaks (Epstein
etal., 2020b; Subiros etal., 2019; Boithias etal., 2016), while some
reviews found insufficient evidence of the effects of drought on
diarrhoea (Levy et al, 2016 ; Asmall etal., 2021; Epstein etal., 2020b;
Subiros etal., 2019; Boithias etal., 2016; Ramesh etal., 2016).
Heavy rainfall and higher than normal temperatures are associated
with increased cholera risk in affected regions (very high confidence).
Cholera is an acute diarrhoeal disease typically caused by the
bacterium Vibrio cholerae that can result in severe morbidity and
mortality. Maximum and minimum temperatures and precipitation
have been negatively associated with cholera cases. Cholera outbreaks
have occurred in several regions after natural disasters, including
cholera incidence increasing three-fold in El Niño-sensitive regions of
Africa (Mpandeli etal., 2018; Amegah etal., 2016; Escobar etal., 2015;
Jutla etal., 2017; Asadgol etal., 2019; Moore etal., 2018; Moore etal.,
2017; Camacho etal., 2018; IPCC, 2019a; Cross-Chapter BoxILLNESS
in Chapter 2; Box3.3).
Heavy rainfall, warmer weather and drought are linked to increased
risks for other GI infections (high confidence). As temperature
increases, bacterial causes of GI infection also appear to increase,
and this association is variably influenced by humidity and rainfall
(Ghazani etal., 2018; Levy, 2016). In New York it has been found that
every 1°C increase in temperature was correlated with a 0.70–0.96%
increase in daily hospitalisation for GI infections (Lin etal., 2016). In
the Philippines, leptospirosis and typhoid fever showed an increase
in incidence following heavy rainfall and flooding events (Matsushita
etal., 2018).
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Health, Wellbeing and the Changing Structure of Communities Chapter 7
Box7.3 | Cascading Risk Pathways Linking Waterborne Disease to Climate Hazards
The causal linkages between climate variability and change and incidence of WBDs follow multiple direct and indirect pathways, often as
part of a cascading series of risks (Semenza, 2020). For example, extreme precipitation can result in a cascading hazard or disease event
with implications of greater magnitude than the initial hazard, especially if there are pre-existing vulnerabilities in critical infrastructure
and human populations (Semenza and Paz, 2021). Intense or prolonged precipitation can flush pathogens in the environment from
pastures and fields to groundwater, rivers and lakes, consequently infiltrating water treatment and distribution systems (Howard etal.,
2016; Khan etal., 2015; Sherpa etal., 2014; Cissé etal., 2016; Kostyla etal., 2015; Chapter 4). Table Box7.3.1 shows the variety and
complexity of pathways between climate hazard and WBD outcomes (Semenza, 2020).
TableBox7.3.1 | Pathways between climate hazard and waterborne disease (WBD) outcomes. Source: Semenza (2020).
Cascading risk pathways from heavy rain and flooding
Storm runoff yields water turbidity, which compromises water treatment efficiency
Storm runoff and floods mobilise and transport pathogens
Overwhelmed or damaged infrastructure compromises water treatment efficiency
Floods overwhelm containment system and discharge untreated wastewater
Floods damage critical water supply and sanitation infrastructure
Floods displace populations towards inadequate sanitation infrastructure
Cascading risk pathways from drought
Low water availability augments travel distance to alternate (contaminated) sources
Intensified demand for and sharing (e.g., with livestock) of limited water resources decreases water availability and quality
Intermittent drinking water supply results in cross-connections with sewer lines and water contamination
Uncovered household water containers are a source of vector breeding
Poor hygiene due to decreased volume of source water and increased concentration of pathogens
Exposure to accumulated human excrements and animal manure
Cascading risk pathways from increasing temperature
Extended transmission season for opportunistic pathogens
Permissive temperature for the replication of marine bacteria
Enhanced pathogen load in animal reservoirs (e.g., chicken)
Pathogen survival and proliferation outside of host
Wildfires during heatwaves degrade water quality
Exposure to contaminated water due to higher water consumption
Behaviour change due to extended season (e.g., food spoilage during barbeque)
Cascading risk pathways from sea level rise
Population displacement due to powerful storm surges
Disruption of drinking water supply and sanitation infrastructure due to inundation
Decline in soil and water quality due to saline intrusion into coastal aquifers
Seawater infiltration into drinking water distribution and sewage lines
Notes:
Examples are purposely not exhaustive and should be considered illustrative.
7.2.2.3 Observed Impacts on Food-Borne Diseases
FBDs refer to any illness resulting from ingesting food that is spoiled
or contaminated by pathogenic bacteria, viruses, parasites, toxins,
pesticides and/or medicines (WHO, 2018b). FBD risks are present
throughout the food chain, from production to consumption, and most
often arise due to contamination at source and from improper food
handling, preparation and/or storage (Smith and Fazil, 2019; Semenza
and Paz, 2021). As with WBDs, FBD outbreaks can follow multiple
causal pathways as climatic risk factors interact with food production
and distribution systems, urbanisation and population growth,
resource and energy scarcity, decreasing agricultural productivity,
price volatility, modification of diet trends, new technologies and the
emergence of antimicrobial resistance (Lake, 2018; Yeni and Alpas,
2017). The burden of FBDs is also linked to malnutrition as reduced
immunity increases susceptibility to various food-borne pathogens and
toxins (FAO, 2020).
A strong association exists between increases in FBDs and high air and
water temperatures and longer summer seasons (very high confidence).
The risks occur through complex transmission pathways throughout
the food chain and the wide range of food-borne pathogens (Cisse,
2019; Hellberg and Chu, 2016; Lake and Barker, 2018; Park et al.,
2018b; Smith and Fazil, 2019). The food-borne pathogens of most
concern are those having low infective doses, a significant persistence
in the environment and high stress tolerance to temperature change
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Chapter 7 Health, Wellbeing and the Changing Structure of Communities
(e.g., enteric viruses, Campylobacter spp., Shiga toxin-producing E.
coli strains, Mycobacterium avium, tuberculosis complexes, parasitic
protozoa and Salmonella) (Lake, 2018; Lake, 2017; Lake and Barker,
2018; Smith and Fazil, 2019; European Food Safety Authority 2020;
Semenza and Paz, 2021). Priority risks include marine biotoxins,
mycotoxins, salmonellosis, vibriosis, transfer of contaminants due to
extreme precipitation, floods, increased use of chemicals in the food
chain (plant protection products, fertilizers, veterinary drugs) and
potential residues in food (European Food Safety Authority 2020;
World Health Organization 2018b).
There is a strong association observed between the increase in average
ambient temperature and increases in Salmonella infections (high
confidence). Most types of Salmonella infections lead to salmonellosis,
while some other types (Salmonella Typhi and Salmonella Paratyphi)
can lead to typhoid fever or paratyphoid fever. The transmission to
humans of the non-typhoidal Salmonella infection, one of the most
widespread FBDs, usually occurs through eating foods contaminated
with animal faeces. Studies conducted in Australia (Milazzo et al.,
2016), New Zealand (Lal etal., 2016), the UK (Lake, 2017), South Korea
(Park etal., 2018a; Park etal., 2018c; Park etal., 2018a), Singapore (Aik
etal., 2018) and Hong Kong, SAR of China (Wang etal., 2018a; Wang
et al., 2018b), have shown that Salmonella outbreaks are strongly
associated with temperature increases.
Significant associations exist between FBDs due to Campylobacter,
precipitation and temperature (medium confidence). The timing of
heat-associated Campylobacteriosis events varies across countries,
with infection rates in the UK appearing to decline immediately
after periods of high rainfall (Djennad etal., 2019; Lake etal., 2019;
Rosenberg etal., 2018; Yun etal., 2016; Weisent etal., 2014). This
suggests the association with climate may be indirect and due to
weather conditions that encourage outdoor food preparation and
recreational activities (Lake, 2017; Semenza and Paz, 2021).
Outbreaks of human and animal Cryptococcus have been reported as
being associated with a combination of climatic factors and shifts in
host and vector populations (Chang and Chen, 2015; Rickerts, 2019). The
prevalence of childhood cryptosporidiosis, which is the second leading
cause of moderate to severe diarrhoea among infants in the tropics
and subtropics, shows associations with population density and rainfall,
with contamination due to Cryptosporidium spp. being 2.61 times
higher during and after heavy rain (Lal etal., 2019; Young etal., 2015;
Khalil etal., 2018). Studies from Ghana, Guinea Bissau, Tanzania, Kenya
and Zambia show a higher prevalence of Cryptosporidium during high
rainfall seasons, with some peaks observed before, at the onset or at
the end of the rainy season (Squire and Ryan, 2017).
7.2.2.4 Respiratory Tract Infections
Climatic risk factors for respiratory tract infections (RTIs) due to
multiple pathogens (bacteria, viruses and fungi) include temperature
and humidity extremes, dust storms, extreme precipitation events and
increased climate variability. Amongst a range of RTIs, pneumonia and
influenza represent a significant disease burden (Ferreira-Coimbra
etal., 2020; Lafond etal., 2021; McAllister etal., 2019; Wang etal.,
2020c). The drivers of pneumonia incidence are complex and include a
range of possible non-climate as well as climate factors. For example,
chronic diseases (e.g., lung disease, chronic obstructive pulmonary
disease (COPD) and asthma), other comorbidities, a weak immune
system, age, gender, community, passive smoking, air pollution and
childhood immunisation may confound the climate pneumonia
relationship (Miyayo etal., 2021).
In temperate regions, the incidence of pneumonia is higher in winter
months, but the exact causes of this seasonality remain debated
(Mirsaeidi etal., 2016). With regards to temperature, various J-shaped,
U-shaped or V-shaped temperature–pneumonia relationships
have been reported in the literature (Huang etal., 2018; Kim etal.,
2016; Liu etal., 2014; Qiu etal., 2016; Sohn etal., 2019) with such
relationships dependent on location. Humidity also appears important
but, like temperature, its effect is not consistent across studies – low
temperatures and low humidity (Davis etal., 2016), high temperatures
and high humidity (Lam etal., 2020) and low temperatures and high
humidity (Miyayo etal., 2021) have all been found to be associated
with an increased incidence of pneumonia.
Day-to-day variations in temperature also appear important.
For Australia, increases in emergency room visits for childhood
pneumonia are associated with sharp temperature drops (Xu etal.,
2014). Large inter-daily changes in temperature are important for
respiratory disease incidence in Guangzhou, China (Lin etal., 2013)
and Shanghai (Lei etal., 2021) while rapidly changing and extreme
temperatures during pregnancy have been linked to childhood
pneumonia (Miao etal., 2017; Zeng etal., 2017; Zheng etal., 2021).
In tropical and subtropical areas of Africa and Asia, pneumonia
incidence has been reported to be higher during the rainy season,
pointing to a positive association between pneumonia patterns and
temperature and precipitation (Chowdhury et al., 2018a; Lim and
Siow, 2018; Paynter etal., 2010).
The degree to which the timing, duration and magnitude of local
influenza virus epidemics is dependent on climate factors is poorly
understood (Lam et al., 2020). Further, a host of non-climate
confounders are likely to influence the incidence of seasonal
influenza (Caini et al., 2018). This poses a number of challenges
for making reliable climate-based epidemiological forecasts for
influenza (Gandon etal., 2016). Although no association between
anomalous climate conditions and influenza have been reported in
some locations (Lam etal., 2020), generally, low winter temperatures
and humidity in temperate regions and periods of high humidity
and precipitation in the tropical and subtropical regions have been
linked to outbreaks of influenza (Deyle etal., 2016; Soebiyanto etal.,
2015; Tamerius et al., 2013). However, the climate sensitivity of
influenza may be more complex than this, with both high and low
humidity; the amount and intensity of precipitation; solar activity
and/or sunshine; and latitude also being important (Axelsen etal.,
2014; Chong etal., 2020b; Geier etal., 2018; Park etal., 2019; Qu,
2016; Smith et al., 2017; Wang etal., 2017c; Zhao et al., 2018a).
Moreover, the shape of the climate variable influenza relationship
may be conditioned on influenza type (Chong etal., 2020a). Further,
distinct periods of weather variability characterised by rapid inter-
daily changes in temperature may act as precursors to influenza
epidemics as has been demonstrated for the marked 2017–2018
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Health, Wellbeing and the Changing Structure of Communities Chapter 7
influenza season and others across the USA (Liu etal., 2020a; Zhao
etal., 2018a). For the eastern Mediterranean, such rapid weather
changes are associated with the ‘Cyprus Low’, with the timing and
magnitude of seasonal influenza related to the interannual frequency
of this particular weather regime (Hochman etal., 2021). Potentially,
large-scale modes of climatic variability such as ENSO and the Indian
Ocean Dipole, which strongly moderate the frequency of weather
regimes in some parts of the world, could affect influenza pandemic
dynamics. However, studies conducted to date report inconsistent
results. Some point to an increased (decreased) severity of seasonal
influenza during El Niño (La Niña) (Oluwole, 2015; Oluwole, 2017),
while others find influenza to be more severe and frequent when
coinciding with La Niña events (Chun etal., 2019; Flahault etal.,
2016; Shaman and Lipsitch, 2013). This raises the possibly of non-
stationary associations between large-scale modes of climatic
variability and influenza dynamics (Onozuka and Hagihara, 2015)
as found for other diseases (Kreppel etal., 2014), something that
might be expected given El Niño’s time-varying impact on global
precipitation and temperature fields and associated impacts on
health outcomes (McGregor and Ebi, 2018).
Cross-Chapter BoxCOVID | COVID-19
Authors: Maarten van Aalst (Netherlands, Chapter 16), Guéladio Cissé (Mauritania/Switzerland/France, Chapter 7), Ayansina Ayanlade
(Nigeria, Chapter 9), Lea Berrang-Ford (United Kingdom/Canada, Chapter 16), Rachel Bezner Kerr (Canada/USA, Chapter 5), Robbert
Biesbroek (Netherlands, Chapter 13), Kathryn Bowen (Australia, Chapter 7), Martina Angela Caretta (Sweden, Chapter 4), So-Min Cheong
(Republic of Korea, Chapter 17), Winston Chow (Singapore, Chapter 6), Mark John Costello (New Zealand/Norway/Ireland, Chapter 11,
CCP1), Kristie Ebi (USA, Chapter 7), Elisabeth Gilmore (USA/Canada, Chapter 14), Bruce Glavovic (South Africa/New Zealand, Chapter
18, CCP2), Walter Leal (Germany, Chapter 8), Stefanie Langsdorf (Germany, TSU), Elena Lopez-Gunn (Spain/United Kingdom, Chapter 4),
Ruth Morgan (Australia, Chapter 4), Aditi Mukherji (India, Chapter 4), Camille Parmesan (France/ United Kingdom /USA, 2), Mark Pelling
(United Kingdom, Chapter 6), Elvira Poloczanska (United Kingdom, TSU), Marie-Fanny Racault (United Kingdom/France, Chapter 3), Diana
Reckien (Germany/Netherlands, Chapter 17), Jan C. Semenza (Sweden, Chapter 7), Pramod Kumar Singh (India, Chapter 18), Stavana E.
Strutz (USA), Maria Cristina Tirado von der Pahlen (Spain/USA, Chapter 7), Corinne Schuster-Wallace (Canada), Alistair Woodward (New
Zealand, Chapter 11), Zinta Zommers (Latvia, Chapter 17)
Introduction
The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes COVID-19, emerged in late 2019, halfway through the
preparation of the IPCC WGII Sixth Assessment Report. This Cross-Chapter Box assesses how the massive shock of the pandemic and
response measures interact with climate-related impacts and risks as well as its significant implications for risk management and climate
resilient development.
COVID-19 and environmental connections
Infectious diseases may emerge and spread through multiple climate-related avenues, including direct effects of climatic conditions
on disease reproduction and transmission and various indirect effects, often interlinked with ecosystem degradation (high confidence).
Climate change is affecting the risk of emerging infectious diseases by contributing to factors that drive the movements of species,
including vectors and reservoirs of diseases, into novel human populations and vice versa (high confidence) (Sections2.4.2.7, 5.2.2.3;
Cross-Chapter Box Illness in Chapter 2; IPCC, 2019b; IPBES 2020). The spillover of some emerging infectious diseases from wildlife into
humans is associated with live animal–human markets, intensified livestock production and climate-related movements of humans
and wild animals into new areas that alter human–animal interactions (Section2.4.2.7; Chapter 3; Sections5.2.2.3, 7.2; Cross-Chapter
BoxILLNESS in Chapter 2; Cross-Chapter BoxMOVING PLATE in Chapter 5).
Human-to-human transmission is the prominent driver in the spread of the COVID-19 pandemic, rather than climatic drivers (high
confidence). There is emerging literature on the environmental determinants of COVID-19 transmission, incidence and mortality rates,
with initial evidence suggesting that temperature, humidity and air pollution contribute to these patterns (Brunekreef etal., 2021; Xiong
etal., 2020; Zhang etal., 2020b; AR6 WGI CCB 6.1: Implications of COVID-19 restrictions for emissions, air quality and climate). Climate
change is altering environmental factors like temperature and seasonality that affect COVID-19 transmission (Choi etal., 2021).
The impact of COVID-19 containment measures resulted in a temporary reduction in greenhouse gas (GHG) emissions and reduced air
pollution (high confidence) (IPCC WGI TS; Arias etal., 2021; AR6 WGI CCB 6.1: Implications of COVID-19 restrictions for emissions, air
quality and climate). However, global and regional climate responses to the radiative effect were undetectable above internal climate
variability due to the temporary nature of emission reductions. They therefore do not result in detectable changes in impacts or risks due
to changes in climate hazards (Arias et al 2021; AR6 WGI CCB 6.1: Implications of COVID-19 restrictions for emissions, air quality and
climate; Naik etal., 2021).
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Chapter 7 Health, Wellbeing and the Changing Structure of Communities
Cascading and compounding risks and impacts
The COVID-19 pandemic posed a severe shock to many socioeconomic systems, resulting in substantial changes in vulnerability and
exposure of people to climate risks (high confidence). The disease and response measures significantly affected human health, economic
activity, food production and availability, health services, poverty, social and gender inequality, education, supply chains, infrastructure
maintenance and the environment. These COVID-19 impacts interact with many risks associated with climate change (IMF, 2020), often
through a cascade of impacts across numerous sectors (van den Hurk etal., 2020). Beyond COVID-19-related mortality and long-term
COVID, mortality from other diseases (some of which may also have a climate-related component), as well as maternal and neonatal
mortality, increased because of disruption in health services (Barach etal., 2020; Maringe etal., 2020; Zadnik etal., 2020; Goyal etal.,
2021). In addition, a rapid rise in poverty has disproportionately affected poorer countries and people (Ferreira etal., 2021), and thus
increased their vulnerability. After many years of steady declines, extreme poverty increased by about 100million people in 2020 (World
Bank, 2021). The effects of the pandemic increased food insecurity and malnourishment, which increased by 1.5percentage points to
around 9.9% in 2020 after being virtually unchanged for the previous five years (FAO etal., 2021).
During the pandemic, extreme weather and climate events such as droughts, storms, floods, wildfires and heatwaves continued, resulting
in disastrous compounding impacts (high confidence). Between March and September 2020, 92 extreme weather events coincided with
the COVID-19 pandemic, affecting an estimated 51.6million people; additionally, 431.7million people were exposed to extreme heat,
and 2.3million people were affected by wildfires (Walton and van Aalst, 2020). The COVID-19 pandemic, in combination with extreme
events, affected disaster preparedness, disaster response and safe evacuations, while physical distancing regulations reduced the capacity
of temporary shelters (UN DRR Asia-Pacific, 2020; Tozier de la Poterie etal., 2020; Shumake-Guillemot, J, et al, 2020; Bose-O’Reilly etal.,
2021). Complex humanitarian emergencies were aggravated, with vulnerable populations facing the combined risks of conflict,
displacement, COVID-19 and climate impacts (FSIN, 2020). Compounding events are not only found in low-income countries but also in
medium- and high-income countries, for instance in the case of COVID-19 and heatwaves (Shumake-Guillemot etal., 2020; Bose-O’Reilly
etal., 2021).
Responses and implications for adaptation and climate resilient development
The pandemic emphasises the inter-connected and compound nature of risks, vulnerabilities and responses to emergencies that
are simultaneously local and global (high confidence). COVID-19 is often considered a more ‘explosive’ risk than the more gradual
anthropogenic climate change. However, many climate-related risks do already appear as severe shocks at smaller scales, and infrequent
or unprecedented extreme weather-related events often warrant similar rapid responses (Dodds etal., 2020; Gebreslassie, 2020; Hynes
etal., 2020; Phillips etal., 2020; Schipper, 2020; Semenza etal., 2021; illustrated in FigureCOVID.1). Individuals, households, sub-
national and national entities, and international organisations had generally delayed responses or denied the pandemic’s severity before
responding at the scale and urgency required, a pattern that resembles the international action required on climate change (Polyakova
etal., 2020; Shrestha etal., 2020).
Improved contingency and recovery planning, including disease mitigation measures, were crucial in responding to the pandemic in
similar ways to those seen in the aftermath of climate-related disasters (Guo etal., 2020; Ebrahim etal., 2020; Baidya etal., 2020;
Shultz etal., 2020; Mukherjee etal., 2020). The pandemic highlighted the lack of global and country-specific capacity to respond to an
unexpected and unplanned event and the need to implement more flexible detection and response systems (Ebi etal., 2021b).
It also exposed underlying vulnerabilities, such as the lack of water access and healthcare in select low- and middle-income countries
and among indigenous and marginalised groups in high-income countries (Section4.4.3; Box4.3; 5.12.1). Increased risks of COVID-19
transmission emerged in crowded areas such as urban settings, refugee camps, detention centres and some workplaces, including in rural
settings (Brauer etal., 2020; Ramos etal., 2020; Staddon etal., 2020; Haddout etal., 2020). Public health responses to the COVID-19
pandemic, such as mandates for social distancing and advice for frequent handwashing, underlined the need for access to water and
sanitation facilities and wastewater management. However, they also sometimes interfered with access, for example, in evacuation and
shelter infrastructure during climate-related disasters (Armitage and Nellums, 2020; Adelodun etal., 2020; Poch etal., 2020; Hallema
etal., 2020; Patel etal., 2020; Espejo etal., 2020).
The experience of COVID-19 demonstrates that many warnings about the risks of the emergence of zoonotic transmission (‘delay is
costly’, ‘adapt early’ and ‘prevention pays’) did not result in sufficient political attention, funding and pandemic prevention. In some
countries, there has been an increased awareness of the risks and the real or perceived trade-offs associated with risk management (e.g.,
economy compared with health and impacts compared with adaptation). Building trust and participatory processes and establishing
Cross-Chapter BoxCOVID (continued)
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Health, Wellbeing and the Changing Structure of Communities Chapter 7
stronger relationships with communities and other civic institutions may enable a recalibration of how the government responds to crises
and society–government relationships more generally (Amat etal., 2020; Deslatte, 2020).
The management of the COVID-19 pandemic has highlighted the value of scientific (including medical and epidemiological) expertise and
the importance of fast, accurate and comprehensive data to inform policy decisions and to anticipate and manage risk (high confidence). It
emphasises the importance of effective communication of scientific knowledge (Semenza etal., 2021), decision-making under uncertainty
and decision frameworks that navigate different values and priorities. Successful policy responses were based on the emerging data,
medical advice and collaboration with a wider set of societal stakeholders beyond public health experts. For instance, experience in
Aotearoa, New Zealand, highlights the importance of pandemic responses attuned to the needs of different sociocultural groups and
Indigenous Peoples in particular. Their strengths-based COVID-19 response goes beyond identifying vulnerabilities to unlocking the
resources, capabilities and potential that might otherwise be latent in communities (McMeeking and Savage, 2020). As far as the value
of information for risk management is concerned, compared to the initial uncertainties regarding COVID-19, data about near- and
longer-term climate-related hazards is generally very good; however, high-quality and dense meteorological data are often still lacking in
lower income countries (Otto etal., 2020). Health data are particularly difficult to obtain in real time, as is the case for biodiversity data,
which has a time lag of years before being made available and for which there is no coordinated monitoring, hampering effective risk
management (Navarro etal., 2017). Therefore, both epidemiological and meteorological forecasts would benefit from more focus on (a)
decision support, (b) conveying uncertainty and (c) capturing vulnerability (Coughlan de Perez etal., 2021).
There is a considerable evidence base of specific actions that have co-benefits for reducing pandemic and climate change risks while
enhancing social justice and biodiversity conservation (high confidence). The pandemic highlighted aspects of risk management that have
long been recognised but are often not reflected in national and international climate policy: the value of addressing structural vulnerability
rather than taking specific measures to control single hazards and drivers of risk and the importance of decision-making capacities and
transparency, the rule of law, accountability and addressing inequities (or social exclusion) (reviewed by Pelling etal. (2021); see also
FigureCOVID.1).
Comprehensive and integrated risk management strategies can enable countries to address both the current pandemic and increase
resilience against climate change and other risks (Reckien, 2021; Semenza etal., 2021; Ebi etal., 2021b). In particular, given their immense
scale, COVID-19 recovery investments may offer an opportunity to contribute to climate resilient development pathways (CRDPs) through
a green, resilient, healthy and inclusive recovery (high confidence) (Sovacool etal., 2020; Rosenbloom and Markard, 2020; Lambert etal.,
2020; Boyle etal., 2020; Bouman etal., 2020; UN DRR Asia-Pacific, 2020; Brosemer etal., 2020; Dodds etal., 2020; Hynes etal., 2020;
Markard and Rosenbloom, 2020; Phillips etal., 2020; Schipper, 2020; Willi etal., 2020; Semenza etal., 2021; Pasini and Mazzocchi, 2020;
Meige etal., 2020; Pelling etal., 2021). However, windows of opportunity to enable such transitions are only open for a limited period
and need to be swiftly acted upon to effect change (high confidence) (Chapter 18; Weible etal., 2020; Reckien, 2021). Initial indications
suggest that only USD1.8 trillion of the greater than USD17 trillion COVID-19-related stimulus financing by G20countries and other major
economies that was committed up until mid-2021 contributed to climate action and biodiversity objectives, with significant differences
between countries and sectors (Vivideconomics, 2021). Moreover, responses to previous crises (e.g., the 2008–2011 global financial
crisis) demonstrate that despite high ambitions during the response phase, opportunities for reform do not necessarily materialise (Bol
etal., 2020; Boin etal., 2005). In addition, heightened societal and political attention to one crisis often comes at the cost of other policy
priorities (high confidence) (Maor, 2018; Tosun etal., 2017), which could affect investments for climate resilient development (Hepburn
etal., 2020; WHO, 2020a; Bateman etal., 2020; Meige etal., 2020; Semenza etal., 2021).
In summary, the emerging literature suggests that the COVID-19 pandemic has aggravated climate-related health risks, demonstrated the
global and local vulnerability to cascading shocks and illustrated the importance of integrated solutions that tackle ecosystem degradation
and structural vulnerabilities in human societies. This highlights the potential and urgency of interventions that reduce pandemic and
climate change risks while enhancing compound resilience, social justice and biodiversity conservation (see FigureCOVID.1).
Cross-Chapter BoxCOVID (continued)
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Chapter 7 Health, Wellbeing and the Changing Structure of Communities
Hazard
Deforestation;
Society/nature alienation
Vulnerability
Fragile livelyhoods;
Fragile health
Exposure
Overcrowded housing;
Inadequate sanitation
Inadequate
response
Exclusive planning;
Uninformed decisions
Risk:
Compound risk to
pandemic and climate
change
Hazard reduction
Reforestation
Conservation of biodiversity
Vulnerability
reduction
Livelihood security;
Healthy lifestyles
Exposure reduction
Adaptive housing;
Adaptive sanitation;
Response
Inclusive planning;
Informal decisions
Resilience:
Compound resilience
to pandemic and
climate change
Compound risk and compound resilience to pandemic and climate change
FigureCOVID.1 | Compound risk and compound resilience to pandemic and climate change. Source: Pelling etal. (2021).
Cross-Chapter BoxCOVID (continued)
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Health, Wellbeing and the Changing Structure of Communities Chapter 7
7.2.2.5 Other Water Shortage and Drought-Associated Diseases
and Health Outcomes
Water shortage and drought are associated with skin diseases
(Schachtel etal., 2021; Lundgren, 2018; Andersen and Davis, 2017;
Kaffenberger et al., 2017; Andersen and Davis, 2017), trachoma
(Ramesh et al., 2016) and violence (Epstein et al., 2020a); more
research is warranted in these areas for future assessment.
7.2.3 Observed Impacts on Non-communicable Diseases
NCDs are those that are not directly transmitted from one person to
another person; they impose the largest disease burden globally. NCDs
constitute approximately 80% of the burden of disease in high-income
countries; the NCD burden is lower in low- and middle-income countries
but are expected to rise (Bollyky etal., 2017). NCDs constitute a large
group of diseases driven principally by environmental, lifestyle and
other factors; those identified as being climate sensitive include non-
infectious respiratory disease, cardiovascular disease (CVD), cancer
and endocrine diseases including diabetes. Additionally, there are
potential interactions between multiple climate-sensitive NCDs and
food security, nutrition and mental health. The literature on climate
change and NCDs continues to develop. More recently, scientists have
identified key gaps in the calculation of the global burden of disease
due to environmental health factors (Shaffer etal., 2019).
7.2.3.1 Cardiovascular Diseases
CVDs are a group of disorders of the heart and blood vessels that
include coronary heart disease, cerebrovascular disease, peripheral
arterial disease, rheumatic heart disease, congenital heart disease, deep
vein thrombosis and pulmonary embolism. CVDs are the leading cause
of death globally and over three quarters of the world’s CVD deaths
now occur in low- and middle-income countries (Roth etal., 2020).
Climate change affects the risk of CVD through high temperatures
and extreme heat (assessed in Section 7.2.4.1) and through other
mechanisms (medium confidence), though the degree to which non-
temperature risks may increase remains unclear. For example, exposure
to air pollutants including PM, ozone (via its precursors), black carbon,
oxides of nitrogen, oxides of sulphur, hydrocarbons and metals can invoke
pro-inflammatory and prothrombotic states, endothelial dysfunction
and hypertensive responses (Giorgini etal., 2017; Stewart etal., 2017).
Winter peaks in CVD events, associated with greater concentrations of
air pollutants, have been reported in a range of countries and climates
(Claeys et al., 2017; Stewart et al., 2017); however, the association
between air pollution, weather and CVD events is complex and seems
to differ between cold and warm months, particularly for gaseous
pollutants such as ozone (Shi etal., 2020).
Climate change is projected to increase the number and severity of
wildfires (Liu etal., 2015b; Youssouf etal., 2014) and the evidence
for wildfire smoke-related CVD morbidity and mortality is suggestive
of increased CVD morbidity and mortality risk (Chen et al., 2021a)
including significant increases in certain cardiovascular outcomes (e.g.,
cardiac arrests) (Dennekamp etal., 2015). CVD risks to highly exposed
populations, such as firefighters, are clearer (Navarro etal., 2019) and
could increase with additional exposure driven by climate change.
Other climate-related mechanisms that may increase CVD risk include
reductions in physical activity related to hot weather (Obradovich etal.,
2017), sleep disturbance (Obradovich et al., 2017) and dehydration
(Lim etal., 2015; Frumkin and Haines, 2019). There is little literature
on how changes in winter weather may affect these risks. Saline
intrusion of groundwater related to sea level rise (Taylor etal., 2012)
may increase the salt intake of affected populations, a risk factor for
hypertension that has been observed to increase blood pressure in
exposed populations (Talukder etal., 2017; Al Nahian etal., 2018).
7.2.3.2 Non-communicable Respiratory Diseases
Lung diseases, including asthma, COPD and lung cancer, comprise the
largest subsets of non-communicable pulmonary disease (Ferkol and
Schraufnagel, 2014). Overall, the global burden of non-communicable
lung disease including all chronic lung disease and lung cancer is
substantial, being responsible for 10.6% of deaths and 5.9% of DALYs
globally in 2019 (Vos etal., 2020).
Several non-communicable respiratory diseases are climate sensitive
based on their exposure pathways (very high confidence). Multiple
exposure pathways contribute to non-communicable respiratory
disease (Deng etal., 2020), some of which are climate-related (Rice
etal., 2014), including mobilisation and transport of dust (Schweitzer
etal., 2018); changes in concentrations of air pollutants such as small
particulates (PM2.5) and ozone formed by photochemical reactions
sensitive to temperature (Hansel et al., 2016); increased wildland
fires and related smoke exposure (Johnston etal., 2002; Reid etal.,
2016); increased exposure to ambient heat driving reduced lung
function and exacerbations of chronic lung disease (Collaco etal.,
2018; Jehn etal., 2013; McCormack etal., 2016; Witt etal., 2015) and
modification of aeroallergen production and duration of exposure
(Ziska etal., 2019).
Burdens of allergic disease, particularly allergic rhinitis and allergic
asthma may be changing in response to climate change (medium
confidence) (D’Amato etal., 2020; Eguiluz-Gracia etal., 2020; Deng
etal., 2020; Demain, 2018). This is supported by evidence showing an
increase in the length of the North American pollen season attributable
to climate change (Ziska etal., 2019), an association between timing
of spring onset and higher asthma hospitalisations presumed to be due
to higher pollen exposure (Sapkota etal., 2020) and other evidence
linking aeroallergen exposure with a worsening burden of allergic
disease (Demain, 2018; Poole etal., 2019).
7.2.3.3 Cancer
Climate change is likely to increase the risk of several malignancies
(high confidence), though the degree to which risks may increase
remains unclear. Cancers, also known as malignant neoplasms,
include a heterogeneous collection of diseases with various causal
pathways, many with environmental influences. Malignant neoplasms
impose a substantial burden of disease globally and are responsible
for slightly more than 10 million deaths and 251 million DALYs
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globally in 2019 (Vos etal., 2020). Climatic hazards affect exposure
pathways for several different chemical hazards associated with
carcinogenesis (Portier et al., 2010). Most relevant literature has
focused on elaborating potential pathways and producing qualitative
or quantitative estimates of effect, though there is limited literature
on current and projected impacts.
The vast majority of elaborated pathways point to increased risk; for
example, there is concern that climate change may alter the fate and
transport of carcinogenic polyaromatic hydrocarbons (Domínguez-
Morueco etal., 2019) and increase mobilisation of carcinogens such
as bromide (Regli etal., 2015), persistent organic pollutants (POPs)
including polychlorinated-biphenyls that have accumulated in areas
contaminated by industrial runoff (Miner etal., 2018) and radioactive
material (Evangeliou etal., 2014). Exposure to these known carcinogens
can occur through multiple environmental media and can be increased
by climate change, for example through increased flooding related
to extreme precipitation events and mobilisation of sediment where
carcinogens have accumulated (León etal., 2017; Santiago and Rivas,
2012). In addition, there is concern that changes in ultraviolet light
exposure related to shifts in precipitation may increase the incidence
of malignant melanoma, particularly for outdoor workers (Modenese
et al., 2018). Other harmful pathways include migration of and
increased exposure to liver flukes, which cause hepatobiliary cancer
(Prueksapanich etal., 2018) and the introduction of infectious diseases
such as schistosomiasis that increase cancer risk due to climate-related
migration (Ahmed etal., 2014). Increased exposure to carcinogenic
toxins via multiple pathways is also a concern. Aflatoxin exposure, for
example, is expected to increase in Europe (Moretti etal., 2019), India
(Shekhar etal., 2018), Africa (Gnonlonfin etal., 2013; Bandyopadhyay
etal., 2016) and North America (Wu etal., 2011). Other carcinogenic
toxins originate from cyanobacteria blooms (Lee etal., 2017a), which
are projected to increase in frequency and distribution with climate
change (Wells etal., 2015; Paerl etal., 2016; Chapra etal., 2017).
7.2.3.4 Diabetes
Individuals suffering from diabetes are at higher risk of heat-related
illness and death (medium confidence). Extreme weather events
and rising temperatures have been found to increase morbidity and
mortality in patients living with diabetes, especially in those with
cardiovascular complications (Méndez-Lázaro etal., 2018; Zilbermint,
2020; Hajat etal., 2017). Evidence suggests that the local heat loss
response of skin blood flow is affected by diabetes-related impairments,
resulting in lower elevations in skin blood flow in response to a heat
or pharmacological stimulus. Thermoregulatory sweating may also be
diminished by type-2 diabetes, impairing the body’s ability to transfer
heat from its core to the environment (Xu etal., 2019b). Higher rates
of doctor consultations by patients with type-2 diabetes and diabetics
with cardiovascular comorbidities have been observed during hot days,
but without evidence of heightened risk of renal failure or neuropathy
comorbidities (Xu etal., 2019b).
People with chronic illnesses are at particular risk during and after
extreme weather events due to treatment interruptions and lack of
access to medication (medium confidence). The impacts of extreme
weather events on the health of chronically ill people are due to a
range of factors including disruption of transport, weakened health
systems including drug supply chains, loss of power and evacuations
of populations (Ryan et al., 2015a). Evacuations also pose specific
health risks to older adults (especially those who are frail, medically
incapacitated or residing in nursing or assisted living facilities) and
may be complicated by the need for concurrent transfer of medical
records, medications and medical equipment (Becquart etal., 2018;
Quast and Feng, 2019; US Global Change Research Program, 2016).
Emergency room visits after Hurricane Sandy rose among individuals
with type-2 diabetes (Velez-Valle etal., 2016).
7.2.4 Observed Impacts on Other Climate-Sensitive
Health Outcomes
7.2.4.1 Heat- and Cold-Related Mortality and Morbidity
Extreme heat events and extreme temperature have well-documented,
observed impacts on health, mortality (very high confidence) and
morbidity (high confidence). AR5 described the thermoregulatory
mechanisms and responses, including acclimatisation, linking heat,
cold and health, and these have been further confirmed by recent
studies and reviews (e.g., Giorgini et al., 2017; Ikaheimo, 2018;
McGregor et al., 2015; Stewart et al., 2017; Schuster et al., 2017;
Zhang etal., 2018b). The health impacts of heat manifest clearly in
periods of extreme heat often codified as heatwaves. For example,
heatwaves across Europe (2003), Russia (2010), India (2015) and
Japan (2018) resulted in significant death tolls and hospitalisations
(McGregor etal., 2017; Hayashida et al., 2019). Heat continues to
pose a significant health risk due to increases in exposure, changes in
the size and spatial distribution of the human population, mounting
vulnerability and an increase in extreme heat events (high confidence)
(Harrington etal., 2017; Liu etal., 2017; Mishra etal., 2017; Rohat
etal., 2019a; Rohat etal., 2019b; Rohat etal., 2019c; Watts etal.,
2019). Some regions are already experiencing heat stress conditions
approaching the upper limits of labour productivity and human
survivability (high confidence). These include the Persian Gulf and
adjacent land areas, parts of the Indus River Valley, eastern coastal
India, Pakistan, northwestern India, the shores of the Red Sea, the
Gulf of California, the southern Gulf of Mexico and coastal Venezuela
and Guyana (Krakauer etal., 2020; Li etal., 2020; Raymond etal.,
2020; Saeed etal., 2021; Xu etal., 2020).
Under a variety of methods, estimates of the world’s population
exposed to extreme heat indicate very large and growing numbers
and an increase since pre-industrial times. For example, Li etal. (2020)
estimate that globally, 1.28 billion people each year experience
heatwave conditions similar to that of the lethal Chicago 1995 event,
compared with 0.99billion people that would be similarly exposed
under a pre-industrial climate. Further, for the 150 most populated
cities of the world, a 500% increase in the exposure to extreme heat
events occurred over the 1980–2017 period (Li etal., 2021), while for
the 1986–2005 period, the total exposure to dangerous heat in Africa’s
173 largest cities was 4.2billion person-days yr
–1
(Rohat etal., 2019a).
Globally the present exposure to heatwave events is estimated to be
14.8billion person-days yr
–1
, with the greatest cumulative exposures
measured in person-days occurring across southern Asia (7.19billion),
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Health, Wellbeing and the Changing Structure of Communities Chapter 7
sub-Saharan Africa (1.43billion), and north Africa and the Middle East
(1.33billion) (Jones etal., 2018).
The country level percentage of mortality attributable to non-
optimum temperature (heat and cold) has been found to range from
3.4 to 11% (Gasparrini etal., 2015; Zhang etal., 2019b). Heat as a
health risk factor has largely been overlooked in low- and middle-
income countries (Campbell etal., 2018; Green etal., 2019; Dimitrova
et al., 2021). For 2019, the GBD report estimates the burden of
DALYs attributable to low temperature was 2.2times greater than
the burden attributable to high temperature. However, this global
figure obscures important regional variations. Countries with a
high sociodemographic index—mainly mid-latitude high-income
temperate to cool climate countries— were found to have a cold-
related burden 15.4times greater than the heat-related burden, while
for warm lower-income regions, such as south Asia and sub-Saharan
Africa, the heat-related burden was estimated to be 1.7times and
3.6 times greater, respectively (Murray et al., 2020). For countries
where data availability permits, there is evidence that extreme
heat (and extreme cold) leads to higher rates of premature deaths
(Armstrong etal., 2017; Cheng etal., 2018; Costa etal., 2017).
Rapid changes and variability in temperatures are observed to increase
heat-related health and mortality risks, the outcomes varying across
temperate and tropical regions (Guo etal., 2016; Cheng etal., 2019; Kim
etal., 2019a; Tian etal., 2019; Zhang etal., 2018b; Zhao etal., 2019).
Several lines of evidence point to a possible decrease in population
sensitivity to heat, albeit mainly for high-income countries (high
confidence), arising from the implementation of heat warning systems,
increased awareness and improved quality of life. (Sheridan and
Allen, 2018). Evidence suggests a general decrease in the impact of
heat on daily mortality (Diaz etal., 2018; Kinney, 2018; Miron etal.,
2015), a decline in the relative risk attributable to heat (Åström etal.,
2018; Barreca etal., 2016; Petkova etal., 2014) and an increase in the
minimum mortality temperature (MMT) (Åström etal., 2018; Folkerts
etal., 2020; Follos etal., 2021; Chung etal., 2018; Todd and Valleron,
2015; Yin etal., 2019). It is difficult to draw conclusions regarding
trends in heat sensitivity for low- to middle-income countries and
specific vulnerable groups as these are under-represented in the
literature (Sheridan and Allen, 2018). Trends in heat sensitivity are
generally believed to be scale and situation dependent, but there is
considerable variability in changes in heat sensitivity as measured
by trends in heat-related mortality or MMT (Follos etal., 2021; Kim
etal., 2019a; Lee etal., 2021), with notable variability across different
population groups (Lu etal., 2021).
Temperature interacts with heat-sensitive physiological mechanisms
via multiple pathways to affect health. In the worst cases, these lead
to organ failure and death (Mora et al., 2017a; Mora et al., 2017b).
Excess deaths during extreme heat events occur predominantly in older
individuals and are overwhelmingly cardiovascular in origin (very high
confidence). A higher occurrence of CVD mortality in association with
prolonged period of low temperatures has been well documented
globally (Giorgini etal., 2017; Stewart etal., 2017); however, there is
growing evidence that cardiovascular deaths are more related to heat
events than cold spells (Chen etal., 2019; Liu etal., 2015a; Bunker etal.,
2016). While there is strong association between ambient temperature
and cardiovascular events globally, there are complex interactions and
modulators of individual response (Wang etal., 2017b). Further, some
CVD morbidity sub-groups such as myocardial infarction (MI) and stroke
hospitalisation display temperature sensitivity while others do not
(Bao etal., 2019; Sun etal., 2018; Wang etal., 2016). Although older
adults have inherent sensitivities to temperature-related health impacts
(Bunker etal., 2016; Phung etal., 2016), children can also be affected by
extreme heat (Xu etal., 2014). Cardiovascular capacity or health is also a
critical determinant of individual health outcomes (Schuster etal., 2017).
Medications to treat CVDs, such as diuretics and beta-blockers, may
impair resilience to heat stress (Stewart etal., 2017). Other mediating
factors in the causal pathway range from alcohol consumption (Cusack
etal., 2011; Epstein and Yanovich, 2019) and obesity (Speakman, 2018)
to pre-existing conditions, such as diabetes and hyperlipidaemia, and
urban characteristics (Chen etal., 2019; Sera etal., 2019).
Under extreme heat conditions, increases in hospitalisations have
been observed for fluid disorders, renal failure, urinary tract infections,
septicaemia, general heat stroke as well as unintentional injuries (Borg
etal., 2017; Phung etal., 2017; Goggins and Chan, 2017; Hayashida
et al., 2019; Hopp et al., 2018; Ito et al., 2018; Kampe et al., 2016;
McTavish etal., 2018; Ponjoan etal., 2017; van Loenhout etal., 2018).
Hospitalisations and mortality due to respiratory disorders also occur
during heat events with the interactive role of air quality being important
for some locations but not others (Krug etal., 2019; Pascal etal., 2021;
Patel etal., 2019). Increased levels of heat-related hospitalisation also
manifest in elevated levels of emergency service calls (Cheng etal., 2016;
Guo, 2017; Papadakis etal., 2018; Williams etal., 2020).
Heat- and cold-related health outcomes vary by location (Dialesandro
etal., 2021; Hu etal., 2019; Phung etal., 2016), suggesting outcomes
are highly moderated by socioeconomic, occupational and other
non-climatic determinants of individual health and socioeconomic
vulnerability (Åström et al., 2020; McGregor et al., 2017; McGregor
etal., 2017; Schuster etal., 2017; Benmarhnia etal., 2015; Watts etal.,
2019) (high confidence). For example, access to air conditioning is an
important determinant of heat-related health outcomes for some
locations (Guirguis etal., 2018; Ostro etal., 2010). Although there is a
paucity of global level studies of the effectiveness of air conditioning for
reducing heat-related mortality, a recent assessment indicates increases
in air conditioning explains only part of the observed reduction in heat-
related excess deaths, amounting to 16.7% in Canada, 20.0% in Japan,
14.3% in Spain and 16.7% in the US (Sera etal., 2020).
Significant effects of heat exposure are evident in sport and work
settings with exertional heat illness leading to death and injury
(Adams and Jardine, 2020). Although most studies of heat-related
sports injuries refer to high-income countries, these point to an
increasing number of heat injuries with widening participation in
sport and an increasing frequency of extreme heat events. The highest
rates of exertional heat illness are reported for endurance type events
(running, cycling and adventure races), American football and athletics
(Gamage et al., 2020; Grundstein et al., 2017; Kerr et al., 2020;
McMahon etal., 2021; Yeargin etal., 2019). The health, safety and
productivity consequences of working in extreme heat are widespread
(Ma etal., 2019; Morabito etal., 2021; Kjellstrom etal., 2019; Orlov
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Chapter 7 Health, Wellbeing and the Changing Structure of Communities
etal., 2020; Smith etal., 2021; Vanos etal., 2019; Varghese etal., 2020;
Williams etal., 2020). Occupational heat strain in outdoor workers
manifests as dehydration, mild reduction in kidney function, fatigue,
dizziness, confusion, reduced brain function, loss of concentration and
discomfort (Al-Bouwarthan etal., 2020; Boonruksa etal., 2020; Habibi
etal., 2021; Levi etal., 2018; Venugopal etal., 2021; Xiang etal., 2014).
In the case of armed forces, a global review of the available literature
points to a slightly higher incidence of heat stroke in men compared
to women but a higher proportion of heat intolerance and greater
risk of exertional heat illness amongst women (Alele etal., 2020).
There is also some evidence that for healthcare workers, the risk of
occupational heat stress grew during the COVID-19 pandemic due to
the need to wear personal protective equipment (Foster etal., 2020;
Lee etal., 2020; Messeri etal., 2021). Based on a systematic review of
the literature, one study estimates global costs from heat-related lost
work time were USD 280billion in 1995 and USD 311billion in 2010,
with low- and middle-income countries and countries with warmer
climates experiencing greater losses as a proportion of gross domestic
project (GDP) (Borg etal., 2021). Other global level assessments note
an increase in the potential hours of work lost due to heat over
the 2000–2018 period; in 2018, 133.6billion potential work hours
were lost, amounting to 45billion hours more than in 2000 (Watts
etal., 2019). For China, heat-related productivity losses have been
estimated at 9.9billion hours in 2019, equivalent to 0.5% of the total
national work hours for that year, with Guangdong province, one of
the warmest regions in China, accounting for almost a quarter of the
losses (Cai etal., 2021).
Wide ranging knowledge regarding the specific detection of heat- and
cold-related mortality/morbidity and its attribution to observed climate
change is lacking. Although there has been an observed increase in
winter-season temperatures for a number of regions, to date there is
variable evidence for a consequential reduction in winter mortality and
susceptibility to cold over time due to milder winters; some countries
demonstrate decreasing trends, while other countries show stable or
even increasing trends in cold-attributable mortality fractions over time
(e.g., Arbuthnott etal. (2020); Åström etal. (2013); Diaz etal. (2019);
Hajat (2017); Hanigan etal. (2021); Lee etal. (2018b)). While there
is a burgeoning literature on the attribution of extreme heat events
to climate change (e.g., Vautard etal. (2020)), the number of studies
that assess the extent to which observed changes in heat-related
mortality may be attributable to climate change is small (Ebi etal.,
2020). During the 2003 European heatwave, anthropogenic climate
change increased the risk of heat-related mortality by approximately
70% and 20% for London and Paris, respectively (Mitchell etal., 2016).
For the severe heat event across Egypt in 2015, the impact on human
discomfort was 69% (±17%) more likely due to anthropogenic climate
change (Mitchell, 2016), and for Stockholm, Sweden, it has been
estimated that mortality due to temperature extremes for 1980 to
2009 was double what would have occurred without climate change
(Åström etal., 2013). To date there has only been one multi-country
attempt to quantify the heat-related human health impacts that have
already occurred due to climate change. Based on an analysis of 732
locations spanning 43countries for the 1991–2018 period, the study
found that on average 37.0% (inter-quartile range 20.5–76.3%) of
warm-season heat-related deaths can be attributed to anthropogenic
climate change, equivalent to an average mortality rate of 2.2/100,000
(median: 1.67/100,000; interquartile range: 1.08–2.34/100,000).
Regions with a high attributed percentage (>50%) include southern
and western Asia (Iran and Kuwait), Southeast Asia (Philippines and
Thailand) and several countries in Central and South America. Those
with lower values (<35%) include Western Europe (the Netherlands,
Germany and Switzerland), eastern Europe (Moldova, the Czech
Republic and Romania), southern Europe (Greece, Italy, Portugal
and Spain), North America (USA) and eastern Asia (China, Japan and
South Korea) (Vicedo-Cabrera etal., 2021). Due to data restrictions,
some of the poorest and most susceptible regions to climate change
and increases in heat exposure, such as west and east Africa (Asefi-
Najafabady etal., 2018; Sylla etal., 2018) and south Asia, could not be
included in the analysis (Mitchell, 2021).
7.2.4.2 Injuries Arising from Extreme Weather Events Other
than Heat and Cold
Injuries comprise a substantial portion of the global burden of disease.
In 2019, injuries comprised 9.82% of total global DALYs and 7.61%
of deaths (Vos etal., 2020). The causal pathways for many injuries,
particularly those from heat and extreme weather events, flooding
and fires, exhibit clear climate sensitivity (Roberts and Arnold,
2007; Roberts and Hillman, 2005), as do some injuries occurring in
occupational settings (Marinaccio et al., 2019; Sheng et al., 2018),
but a comprehensive assessment of climate sensitivity in injury causal
pathways has not been done. Certain groups, including Indigenous
Peoples, children and the elderly (Ahmed etal., 2020) are at greater
risk for a wide range of injuries. Extreme events impose substantial
disease burden directly as a result of traumatic injuries, drowning and
burns and large mental health burdens associated with displacement
(Fullilove, 1996), depression and post-traumatic stress disorder (PTSD),
but the overall injury burden associated with extreme weather is not
known. It is known that the Asia-Pacific region has experienced the
highest relative burden of injuries from extreme weather in recent
decades (Hashim and Hashim, 2016).
Extreme weather imposes a substantial morbidity and mortality burden
that is quite variable by location and hazard. The proportion of this
burden related specifically to injuries is not established. From 1998 to
2017 there were 526,000 deaths from 11,500 extreme weather events,
and the average annual attributable all-cause mortality incidence
in the ten most affected countries was 3.5 per 100,000 population
(Eckstein etal., 2017). Rates can be much higher; mortality incidence
in Puerto Rico and Dominica from extreme weather were 90.2 and
43.7 per 100,000 population in 2017, respectively (Eckstein et al.,
2017). Not all of these deaths are from injuries, and the proportion
of mortality and morbidity associated with injuries varies by location
and hazard. One review found that one-year post-event prevalence
rates for injuries associated with extreme events (floods, droughts,
heatwaves and storms) in developing countries ranged from 1.4% to
37.9% (Rataj etal., 2016). Other literature has documented an increase
in the risk of motor vehicle accidents in association with extreme
precipitation (Liu etal., 2017; Stevens etal., 2019), temperature (Leard
and Roth, 2019) and sandstorms (Islam etal., 2019) and an increased
risk of traumatic occupational injuries associated with temperature
extremes, particularly extreme heat, likely from fatigue and decreased
psychomotor performance (Varghese etal., 2019).
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Health, Wellbeing and the Changing Structure of Communities Chapter 7
There is clear evidence of climate sensitivity for multiple injuries from
floods, fires and storms, but there is a need for additional evidence
regarding the current injury burden attributable to climate change. It is
as likely as not that climate change has increased the current burden
of disease from injuries related to extreme weather, particularly in low-
income settings (low confidence). Approximately 120million people
are exposed to coastal flooding annually (Nicholls etal., 2007), causing
an estimated 12,000 deaths (Shultz etal., 2005), and there is significant
concern for worsening flooding associated with climate change (Shultz
etal., 2018a; Shultz etal., 2018b; Woodward and Samet, 2018) but
very limited quantification of attributable burden. A range of adverse
health outcomes has been identified in a study of fires in sub-zero
temperatures that are thought to be increasing in frequency due to
climate change (Metallinou and Log, 2017).
7.2.4.3 Observed Impacts on Maternal, Foetal and Neonatal
Health
Maternal and neonatal disorders accounted for 3.7% of total global
deaths and 7.8% of global DALYs in 2019 (Vos etal., 2020). Children
and pregnant women have potentially higher rates of vulnerability
and/or exposure to climatic hazards, extreme weather events and
undernutrition (Garcia and Sheehan, 2016; Sorensen et al., 2018;
Chersich et al., 2018). Available evidence suggests that heat is
associated with higher rates of pre-term birth (Wang et al., 2020),
low birthweight, stillbirth, neonatal stress (Cil and Cameron, 2017;
Kuehn and McCormick, 2017) and adverse child health (Kuehn and
McCormick, 2017). Extreme weather events are associated with
reduced access to prenatal care, unattended deliveries (Abdullah
etal., 2019) and decreased paediatric healthcare access (Haque etal.,
2019).
7.2.4.4 Observed Impacts on Malnutrition
Climate variability and change contribute to food insecurity that can
lead to malnutrition, including undernutrition, overweight and obesity,
and to disease susceptibility, particularly in low- and middle-income
countries (high confidence). Since AR5, analyses of the links between
climate change and food expanded beyond undernutrition to include
the impacts of climate change on a wider set of diet- and weight-
related risk factors and their impacts on NCDs, along with the role
of dietary choices for GHG emissions (IPCC, 2019b) including dietary
inadequacy (deficiencies, excesses or imbalances in energy, protein
and micronutrients), infections and sociocultural factors (Global
Nutrition Report 2020). Undernutrition exists when a combination of
insufficient food intake, health, and care conditions results in one or
more of the following: underweight for age, short for age (stunted),
thin for height (wasted), or functionally deficient in vitamins and/
or minerals (micronutrient malnutrition or ‘hidden hunger’). Food
insecurity and poor access to nutrient-dense food contribute not only
to undernutrition but also to obesity and susceptibility to NCDs in
low- and middle-income countries (FAO etal., 2018; Swinburn etal.,
2019).
Globally, more than 690million people are undernourished, 144million
children are stunted (chronic undernutrition), 47million children are
wasted (acute undernutrition), and more than 2billion people have
micronutrient deficiencies (FAO, 2020). More than 135million people
across 55countries experienced acute hunger requiring urgent food,
nutrition and livelihood assistance in 2019 (FSIN/GNAFC, 2020).
The COVID-19 pandemic is projected to increase the number of
acutely food insecure people to 270million people (FSIN, 2020) and
worsen malnutrition levels (FAO etal., 2020; Rippin etal., 2020). The
relationships between climate change and obesity vary based on
geography, population sub-groups and/or stages of economic growth
and population growth (An etal., 2017). Increasing temperatures could
contribute to obesity through reduced physical activity, increased
prices of produce or shifts in eating patterns of populations towards
more processed foods (An etal., 2018). In the largest global study
to date exploring the connections between child diet diversity and
recent climate, data from 19countries in six regions (Asia, Central
America, South America, north Africa, southeast Africa and west Africa)
indicated significant reductions in diet diversity associated with higher
temperatures and significant increases in diet diversity associated with
higher precipitation (Niles etal., 2021).
Climate change can affect the four aspects of food security: food
production and availability, stability of food supplies, access to food
and food utilisation (IPCC, 2019b). Access to sufficient food does not
guarantee nutrition security. Extreme weather and climate events
can result in inadequate or insufficient food consumption, increasing
susceptibility to infectious diseases (Rodriguez-Llanes etal., 2016; Gari
etal., 2017; Kumar etal., 2016; Lazzaroni and Wagner, 2016) but also
to being overweight or obese and increasing susceptibility to non-
communicable diseases in low- and middle-income countries (FAO,
2018; Swinburn etal., 2019).
Nearly half of all deaths in children under five years of age are
attributable to undernutrition, putting children at greater risk of dying
from common infections. Undernutrition in the first 1,000days of a
child’s life can lead to stunted growth, which can result in impaired
cognitive ability and reduced future school and work performance
and the associated costs of stunting in terms of lost economic growth
can be of the order of 10% of GDP yr
–1
in Africa (UNICEF/WHO/WBG,
2019).
At the same time, diseases associated with high-calorie, unhealthy diets
are increasing globally, with 38.3million overweight children under
five years of age (Global Nutrition Report, 2018), 2.1billion overweight
or obese adults and the global prevalence of diabetes almost doubling
in the past 30years (Swinburn etal., 2019). Unbalanced diets, such
as diets low in fruits and vegetables and high in red and processed
meat, are the number one risk factor for mortality globally and in most
regions (Gakidou etal., 2018; Afshin etal., 2019).
Socioeconomic factors that mediate the influence of climate change on
nutrition include cultural and societal norms; governance, institutions,
policies and fragility; human capital and potential; and social position
and access to healthcare, education and food aid (Rozenberg, 2017;
Alkerwi etal. 2015; Tirado, 2017; FAO etal., 2018; Global Nutrition
Report 2020). Extreme events may affect access to adequate diets,
leading to malnutrition and increasing the risk of disease (Beveridge
etal., 2019; Rodriguez-Llanes etal., 2016; Gari etal., 2017; Kumar
etal., 2016; Lazzaroni and Wagner, 2016; Thiede and Gray, 2020).
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7.2.4.5 Observed Impacts on Exposure to Chemical
Contaminants
Climate change in northern regions, including Arctic ecosystems,
is causing permafrost to thaw, creating the potential for mercury
(Hg) to enter the food chain (medium agreement, low evidence) as
methyl mercury (MeHg), which is highly neurotoxic and nephrotoxic
and bioaccumulates and biomagnifies throughout the food chain via
dietary uptake of fish, seafood and mammals. Mercury methylation
processes in aquatic environments have been found to be exacerbated
by ocean warming, coupled with more acidic and anoxic sediments
(FAO, 2020). Consumption of mercury-contaminated fish has been
found to be linked to neurological disorders due to methyl mercury
poisoning (i.e., Minamata disease) that is associated with climate
change-contaminant interactions that alter the bioaccumulation and
biomagnification of toxic and fat-soluble persistent organic pollutants
and polychlorinated biphenyls (PCBs) (Alava etal., 2017) in seafood
and marine mammals (medium confidence). Indigenous Peoples have
a higher exposure to such risks because of the accumulation of such
toxins in traditional foods (J.J. etal., 2017). Contamination of food with
PCBs and dioxins has a range of adverse health impacts (Lake etal.,
2015).
Chapter 5 (Sections 5.4.3, 5.5.2.3, 5.8.1, 5.8.2, 5.8.3, 5.9.1, 5.11.1,
5.11.3, 5.12.3) discusses the possible impacts of climate change on
food safety, including exposure to toxigenic fungi, PCBs and other
POPs, mercury and harmful algal blooms.
Climate change may affect animal health management practices,
potentially leading to an increased use of pesticides or veterinary drugs
(such as preventive antimicrobials) that could result in increased levels
of residues in foods (high agreement, medium/low evidence) (Beyene
et al., 2015; FAO and WHO, 2018; European Food Safety Authority,
2020; MacFadden etal., 2018).
7.2.5 Observed Impacts on Mental Health and Well-Being
7.2.5.1 Observed Impacts on Mental Disorders
A wide range of climatic events and conditions have observed and
detrimental impacts on mental health (very high confidence). The
pathways through which climatic events affect mental health are
varied, complex and inter-connected with other non-climatic influences
that create vulnerability (Figure 7.6). The climatic exposure may be
direct, such as experiencing an extreme weather event or prolonged
high temperatures, or indirect, such as mental health consequences
of undernutrition or displacement. Exposure may also be vicarious,
with people experiencing decreased mental health associated with
observing the impact of climate change on others or simply by learning
about climate change. Non-climatic moderating influences range
from an individual’s personality and pre-existing conditions, to social
support, and to structural inequities (Gariepy et al., 2016; Hrabok
etal., 2020; Nagy etal., 2018; Silva etal., 2016b). Depending on these
background and contextual factors, similar climatic events may result
in a range of potential mental health outcomes, including anxiety,
depression, acute traumatic stress, PTSD, suicide, substance abuse and
sleep problems, with conditions ranging from being mild in nature to
those that require hospitalisation (Berry etal., 2010; Cianconi etal.,
2020; Clayton etal., 2017; Ruszkiewicz etal., 2019; Bromet etal., 2017;
Lowe, 2019). The line between mental health and more general well-
being is permeable, but in this section we refer to diagnosable mental
disorders—conditions that disrupt or impair normal functioning
through impacts on mood, thinking or behaviour.
There is an observable association between high temperatures and
mental health decrements (high confidence), with an additional
possible influence of increased precipitation (medium agreement,
medium evidence). Heat-associated mental health outcomes include
suicide (Williams etal., 2015a; Carleton, 2017; Burke etal., 2018; Kim
etal., 2019b; Thompson etal., 2018; Schneider etal., 2020; Cheng
etal., 2021; Baylis etal., 2018; Obradovich etal., 2018); psychiatric
hospital admissions and emergency room visits for mental disorders
(Hansen etal., 2008; Wang etal., 2014; Chan etal., 2018; Mullins and
White, 2019; Yoo etal., 2021); experiences of anxiety, depression and
acute stress (Obradovich etal., 2018; Mullins and White, 2019); and
self-reported mental health (Li etal., 2020). In Canada, Wang etal.
(2014) found an association between mean heat exposure of 28°C and
greater hospital admissions within 0 to 4days for mood and behavioural
disorders (including schizophrenia, mood and neurotic disorders). A US
study found mental health problems increased by 0.5% when average
temperatures exceed 30°C, compared to averages between 25°C
and 30°C; a 1°C warming over five years was associated with a 2%
increase in mental health problems (Obradovich etal., 2018). Another
study found a 1°C rise in monthly average temperatures over several
decades was associated with a 2.1% rise in suicide rates in Mexico and
a 0.7% rise in suicide rates in the USA (Burke etal., 2018). A systematic
review of published research using a variety of methodologies from
19countries (Thompson etal., 2018) found an increased risk of suicide
associated with a 1°C rise in ambient temperature.
Discrete climate hazards including storms (Kessler etal., 2008; Boscarino
et al., 2013; Boscarino et al., 2017; Obradovich et al., 2018), floods
(Baryshnikova and Pham, 2019), heatwaves, wildfires and drought
(Hanigan etal., 2012; Carleton, 2017; Zhong etal., 2018; Charlson etal.,
2021) have significant negative consequences for mental health (very
high confidence). A large body of research identifies the impacts of
extreme weather events on PTSD, anxiety and depression; much of the
research has been done in the USA and the UK, but a growing number
of studies find evidence for similar impacts on mental health in other
countries, including Spain (Foudi etal., 2017), Brazil (Alpino etal., 2016),
Chile (Navarro etal., 2016), Small Island Developing States (Kelman
etal., 2021) and Vietnam (Pollack etal., 2016). Approximately 20–30%
of those who live through a hurricane develop depression and/or PTSD
within the first few months following the event (Obradovich etal., 2018;
Schwartz etal., 2015; Whaley, 2009), with similar rates for people who
have experienced flooding (Waite etal., 2017; Fernandez etal., 2015).
Studies conducted in South America and Asia indicate an increase in
PTSD and depressive disorders after extreme weather events (Rataj
etal., 2016). Evidence is lacking for African countries (Otto etal., 2017).
Children and adolescents are particularly vulnerable to post-traumatic
stress after extreme weather events (Brown etal., 2017; Hellden etal.,
2021; Kousky, 2016), and increased susceptibility to mental health
problems may linger into adulthood (Maclean etal., 2016).
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Health, Wellbeing and the Changing Structure of Communities Chapter 7
Climate change impacts on mental health and adaptation responses
2
1
Hazard
Acute events
(e.g. storms, floods, wildfires,
extreme heat)
Chronic changes
(e.g. drought, sea level rise, sea ice
loss, changing climate normals)
Vulnerability
Pre-existing health conditions
Socio-economic inequities
Gender
Age
Occupation
Exposure
Direct exposure(s)
Indirect exposure(s)
(e.g. displacement, food systems
disruption, occupational loss)
Vicarious exposure(s)
(e.g. observed experiences of others,
media depictions of climate change)
Key adaptation responses
Scale of adaptation
Institutional
State and non-state actors:
effective mental health systems, planning and
preparedness, informed policies, early
intervention
Local governments:
planning, design, green infrastructure
Community
- Supportive social networks, effective
information channels
Individuals
- awareness, preparedness, mental health
support, nature-based therapy
3
4
Risks to mental health and wellbeing
5
2. Vulnerability
Physiological factors
Social factors
3.Exposure
Direct exposure(s)
Indirect exposure(s)
Vicarious exposure(s)
4. Response
Institutional
Community
Individuals
1. Hazard
Acute events
Chronic changes
5. Risks
to mental health
and wellbeing
Mental illness
[e.g., PTSD, depression, suicide]
Diminished wellbeing
[e.g., stress, climate anxiety, cognitive impairment )
Diminished social relations
[e.g., loss of culture, interpersonal violence)
Figure7.6 | Climate change impacts on mental health and key adaptation responses.
PTSD: Post traumatic stress disorder.
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Wildfires have observed negative impacts on mental health (high
confidence). This is due to the trauma of the immediate experience
and/or subsequent displacement and evacuation (Dodd etal., 2018;
Brown etal., 2019; Psarros etal., 2017; Silveira etal., 2021b). Sub-
clinical outcomes, such as increases in anxiety, sleeplessness or
substance abuse are reported in response to wildfires and extreme
weather events, with impacts being pronounced among those who
experience greater losses or are more directly exposed to the event;
this may include first responders.
Mental health impacts can emerge as result of climate impacts on
economic, social and food systems (high confidence). For example,
malnutrition among children has been associated with a variety of
mental health problems (Adhvaryu et al., 2019; Hock et al., 2018;
Yan etal., 2018), as has food insecurity among adults (Lund et al.,
2018). The economic impacts of droughts have been associated with
increases in suicide, particularly among farmers (Carleton, 2017;
Edwards etal., 2015; Vins etal., 2015); those whose occupations are
likely to be affected by climate change report that it is a source of
stress that is linked to substance abuse and suicidal ideation (Kabir,
2018). Studies of Indigenous Peoples often describe food insecurity or
reduced access to traditional foods as a link between climate change
and reduced mental health (Middleton etal., 2020b). The loss of family
members, for example due to an extreme weather event, increases
the risk of mental illness (Keyes etal., 2014). Individuals in low- and
middle-income countries may be more severely impacted due to lesser
access to mental health services and lower financial resources to help
cope with impacts compared with high-income countries (Abramson
etal., 2015).
Anxiety about the potential risks of climate change and awareness
of climate change itself can affect mental health even in the absence
of direct impacts (low confidence). There is a need for more evidence
about the prevalence or severity of climate change-related anxiety,
sometimes called ecoanxiety, but national surveys in the USA, Europe
and Australia show that people express high levels of concern and
perceived harm associated with climate change (Steentjes et al.,
2017; Clayton and Karazsia, 2020; Cunsolo and Ellis, 2018; Helm
etal., 2018; Leiserowitz etal., 2017; Reser etal., 2012; Steentjes etal.,
2017). In a US sample, perceived ecological stress, defined as personal
stress associated with environmental problems, predicted depressive
symptoms (Helm etal., 2018); in a sample of Filipinos, climate anxiety
was correlated with lower mental health (Reyes etal., 2021) and a
non-random study in 25 countries showed positive correlations
between negative emotions about climate change and self-rated
mental health (Ogunbode etal., 2021). However, an earlier study found
no correlation between climate change worry and mental health issues
(Berry and Peel, 2015). Because the perceived threat of climate change
is based on subjective perceptions of risk and coping ability as well
as on experiences and knowledge (Bradley etal., 2014), even people
who have not been directly affected may be stressed by a perception
of looming danger (Clayton and Karazsia, 2020). Not surprisingly,
those who have directly experienced some of the effects of climate
change may be more likely to show such responses. Indigenous
Peoples, whose culture and well-being tend to be strongly linked to
local environments, may experience mental health effects associated
with changes in environmental risks; studies suggest connections to an
increase in depression, substance abuse or suicide in some Indigenous
Peoples (Canu etal., 2017; Cunsolo Willox etal., 2013; Middleton etal.,
2020b; Jaakkola etal., 2018).
7.2.5.2 Observed Impacts on Well-Being
Overall, research suggests that climate change has already had
negative effects on subjective well-being (medium confidence).
Climate change can affect well-being through a number of pathways,
including loss of access to green and blue spaces due to damage
from storms, coastal erosion, drought or wildfires; heat; decreased air
quality; and disruptions to one’s normal pattern of behaviour, residence,
occupation or social interactions (Hayward and Ayeb-Karlsson, 2021).
For example, substantial evidence shows a negative correlation
between air pollution and subjective well-being or happiness (Apergis,
2018; Cunado and de Gracia, 2013; Lu, 2020; Luechinger, 2010;
Menz and Welsch, 2010; Orru etal., 2016; Yuan etal., 2018; Zhang
et al., 2017a); in the reverse direction, there is evidence not only
that time in nature but more specifically a feeling of connectedness
to nature are both associated with well-being (Martin etal., 2020)
and healthy ecosystems offer opportunities for health improvements
(Pretty and Barton, 2020). Negative emotions such as grief—often
termed ‘solastalgia’ (Albrecht etal., 2007)—are associated with the
degradation of local or valued landscapes (Eisenman etal., 2015; Ellis
and Albrecht, 2017; Polain etal., 2011; Tschakert etal., 2017; Tschakert
et al., 2019), which may threaten cultural rituals, especially among
Indigenous Peoples (Cunsolo and Ellis, 2018; Cunsolo et al., 2020).
Studies conducted in the Solomon Islands and Tuvalu found qualitative
and quantitative evidence of experiences of climate change and worry
about the future, with negative impacts on respondents’ well-being
(Asugeni etal., 2015; Gibson etal., 2020).
Heat is one of the best-studied aspects of climate change observed
to reduce well-being (high confidence). Higher summer temperatures
are associated with decreased happiness and ratings of well-being
(Carleton and Hsiang, 2016; Miles-Novelo and Anderson, 2019;
Connolly, 2013; Noelke etal., 2016; Baylis etal., 2018; Moore etal.,
2019; Wang etal., 2020b). A study of 1.9million Americans (Noelke
etal., 2016) found that exposure to one day averaging 21°C–27°C was
associated with reduced well-being by 1.6% of a standard deviation
and days above 32°C were associated with reduced well-being
by 4.4% of a standard deviation relative to a reference interval of
10°C–16°C. A similar relationship between heat and mood has been
observed in China, where expressed mood began to decrease when
the average daily temperature was over 20°C (Wang etal., 2020b). The
causal mechanism is unclear but could be due to impacts on health,
economic costs or social interactions (Belkin and Kouchaki, 2017;
Osberghaus and Kühling, 2016) or reduced quality or quantity of sleep
(Fujii etal., 2015; Obradovich etal., 2017; Obradovich and Migliorini,
2018). Heat has also been associated with inter-personal and inter-
group aggression and increases in violent crime (Heilmann etal., 2021;
Mapou etal., 2017; Tiihonen etal., 2017). For the most part, studies
have measured daily response to average daily temperatures and are
unable to predict whether the effect is cumulative in response to a
sequence of unusually warm days. However, there is no evidence that
adaptation occurs over time to eliminate the negative response to very
warm temperatures (Moore etal., 2019). Some research has found
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Health, Wellbeing and the Changing Structure of Communities Chapter 7
a negative effect of extreme cold on well-being (Yoo etal., 2021);
increasing winter temperatures associated with climate change could
serve to compensate for the impact of increased summer temperatures.
However, the effect of high temperatures is typically found to be
stronger than the effect of low temperatures, and in some cases no
detrimental impacts of cold weather are found (Almendra etal., 2019;
Mullins and White, 2019).
Climate change also threatens well-being defined in terms of
capabilities or the capacity to fulfil one’s potential and fully participate
in society. Heat can limit labour capacity; one study estimated that
45billion hours of labour productivity were lost in 2018 compared
to 2000 due to high temperatures (Watts et al., 2019). Both heat
and air pollution also impair human capabilities through a negative
effect on cognitive performance (Taylor etal., 2016b) and even impair
skills acquisition, reducing the ability to learn (Park et al., 2021)
and affecting marginalised groups more strongly (Park etal., 2020),
although findings are inconsistent and depend in part on the nature of
the task (low confidence).
Systematic reviews have found an association between higher
ambient levels of fine airborne particles with cognitive impairment
in the elderly and with behavioural problems (related to impulsivity
and attention problems) in children (Power etal., 2016; Yorifuji etal.,
2017; Younan etal., 2018; Zhao etal., 2018b) (medium confidence).
Malnutrition has also been associated with reduced educational
achievement and long-term decrements in cognitive function
(Acharya etal., 2019; Asmare etal., 2018; Na etal., 2020; Kim etal.,
2017; Talhaoui etal., 2019).
7.2.6 Observed Impacts on Migration
Consistent with peer-reviewed scholarship and with the United
Nations Framework Convention on Climate Change (UNFCCC) Cancun
Adaptation Framework section 14(f) and the Paris Agreement, this
Chapter assesses the impacts of climate change on four types of
migration: (a) adaptive migration (i.e., where migration is an outcome
of individual or household choice), (b) involuntary migration and
displacement (i.e., where people have few or no options except to
move), (c) organised relocation of populations from sites highly exposed
to climatic hazards and (d) immobility (i.e., an inability or unwillingness
to move from areas of high exposure for cultural, economic or social
reasons) (Cross-Chapter BoxMIGRATE in Chapter 7).
A general theme across studies from all regions is that climate-related
migration outcomes are diverse (high confidence) and may be manifest
as decreases or increases in migration flows, and may lead to changes
in the timing or duration of migration and to changes in migration
source locations and destinations. Multi-country studies of climatic
impacts on migration patterns in Africa have found that migration
exhibits weak, inconsistent associations with variations in temperature
and precipitation and that migration responses differ significantly
between countries and between rural and urban areas (Gray and Wise,
2016; Mueller etal., 2020). Multi-directional findings such as these are
also common in single-country studies from multiple regions (Call etal.,
2017; Nawrotzki etal., 2017; Cattaneo etal., 2019; Kaczan and Orgill-
Meyer, 2020). The diversity of potential migration and displacement
outcomes reflects (a) the variable nature of climate hazards in terms
of the rate of onset, intensity, duration, spatial extent and severity of
damage caused to housing, infrastructure and livelihoods and (b) the
wide range of social, economic, cultural, political and other non-climatic
factors that influence exposure, vulnerability, adaptation options
and the contexts in which migration decisions are made (Neumann
and Hermans, 2015; McLeman, 2017; Barnett and McMichael, 2018;
Cattaneo etal., 2019; Hoffmann etal., 2020) (high confidence).
Weather events and climate conditions can act as direct drivers of
migration and displacement (e.g., destruction of homes by tropical
cyclones) and as indirect drivers (e.g., rural income losses and/or
food insecurity due to heat- or drought-related crop failures that
in turn generate new population movements) (high confidence).
Extreme storms, floods and wildfires are strongly associated with
high levels of short- and long-term displacement, while droughts,
extreme heat and precipitation anomalies are more likely to stimulate
longer-term changes in migration patterns (Kaczan and Orgill-Meyer,
2020; Hoffmann et al., 2020). Longer-term environmental changes
attributable to anthropogenic climate change—such as higher
average temperatures, desertification, land degradation, biodiversity
loss and sea level rise—have had observed effects on migration
and displacement in a limited number of locations in recent decades
but are projected to have wider-scale impacts on future population
patterns and migration, and are therefore assessed in Section7.3.2
(Projected Risks).
The diversity of potential migration and displacement outcomes
reflects the scale and physical impacts of specific climate hazard
events and the wide range of social, economic, cultural, political
and other non-climatic factors that influence exposure, vulnerability,
adaptation options and the contexts in which migration decisions are
made (high confidence). The diversity in drivers, contexts and outcomes
makes it difficult to offer simple generalisations about the relationship
between climate change and migration. The characteristics of climatic
drivers vary in terms of the rate of onset, intensity, duration, spatial
extent and severity of damage caused to housing, infrastructure and
livelihoods; the potential migration responses to these are further
mediated by cultural, demographic, economic, political, social and
other non-climatic factors operating across multiple scales (Neumann
and Hermans, 2015; McLeman, 2017; Barnett and McMichael, 2018;
Cattaneo etal., 2019; Hoffmann etal., 2020).
Climate-related migration and displacement outcomes display high
variability in terms of migrant success, often reflecting pre-existing
socioeconomic conditions and household wealth (high confidence).
The decision to migrate or remain in place when confronted by
climatic hazards is strongly influenced by the range and accessibility
of alternative, in situ (i.e., non-migration) adaptation options that may
be less costly or disruptive (Cattaneo etal., 2019). Migration decisions
(whether climate-related or not) are typically made at the individual or
household level and are influenced by a household’s perceptions of risk,
social networks, wealth, age structure, health and livelihood choices
(Koubi etal., 2016b; Gemenne and Blocher, 2017). Households with
greater financial resources and higher levels of educational attainment
have greater capacity to adapt in situ (Cattaneo and Massetti, 2019;
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Chapter 7 Health, Wellbeing and the Changing Structure of Communities
Cross-Chapter BoxMIGRATE | Climate-Related Migration
Authors: David Wrathall (USA, Chapter 8), Robert McLeman (Canada, Chapter 7), Helen Adams (United Kingdom, Chapter 7), Ibidun
Adelekan (Nigeria, Chapter 9), Elisabeth Gilmore (USA/Canada, Chapter 14), François Gemenne (Belgium, Chapter 8), Nathalie Hilmi
(Monaco, Chapter 18), Ben Orlove (USA, Chapter 17), Ritwika Basu (India/United Kingdom, Chapter 18), Halvard Buhaug (Norway,
Chapter 16), Edwin Castellanos (Guatemala, Chapter 12), David Dodman (United Kingdom, Chapter 6), Felix Kanungwe Kalaba (Zambia,
Chapter 9), Rupa Mukerji (Switzerland/India, Chapter 18), Karishma Patel (USA, Chapter 1), Chandni Singh (India, Chapter 10), Philip
Thornton (United Kingdom, Chapter 5), Christopher Trisos (South Africa, Chapter 9), Olivia Warrick (New Zealand, Chapter 15), Vishnu
Pandey (Nepal, Chapter 4)
Key messages on migration in this report
Migration is a universal strategy that individuals and households undertake to improve well-being and livelihoods in response to
economic uncertainty, political instability and environmental change (high confidence). Migration, displacement and immobility that
occur in response to climate hazards are assessed in general in Chapter 7, with specific sectoral and regional dimensions of climate-
related migration assessed in sectoral and regional Chapters 5 to 15 (TableMIGRATE.1 in Chapter 7) and involuntary immobility and
displacement being identified as representative key risks in Chapter 16 (Sections16.2.3.8, 16.5.2.3.8). Since AR5 there has been a
considerable expansion in research on climate–migration linkages, with five key messages from the present assessment report warranting
emphasis.
Climatic conditions, events and variability are important drivers of migration and displacement (high confidence) (TableMIGRATE.1 in
Chapter 7), with migration responses to specific climate hazards being strongly influenced by economic, social, political and demographic
processes (high confidence) (Sections7.2.6, 8.2.1.3). Migration is among a wider set of possible adaptation alternatives and often emerges
when other forms of adaptation are insufficient (Sections5.5.1.1, 5.5.3.5, 7.2.6, 8.2.1.3, 9.7.2). Involuntary displacement occurs when
adaptation alternatives are exhausted or not viable and reflects non-climatic factors that constrain adaptive capacity and create high
levels of exposure and vulnerability (high confidence) (Cross-Chapter BoxSLR in Chapter 3; Sections4.3.7, 7.2.6; Box8.1; Section10.3;
Box14.7). There is strong evidence that climatic disruptions to agricultural and other rural livelihoods can generate migration (high
confidence) (Sections5.5.4, 8.2.1.3, 9.8.3; Box9.8).
Specific climate events and conditions may cause migration to increase, decrease or flow in new directions (high confidence), and the
more agency migrants have (i.e., the degree of voluntarity and freedom of movement), the greater the potential benefits for sending and
receiving areas (high agreement, medium evidence) (Sections5.5.3.5, 7.2.6, 8.2.1.3; Box12.2). Conversely, displacement or low-agency
migration is associated with poor outcomes in terms of health, well-being and socioeconomic security for migrants and returns fewer
benefits to sending or receiving communities (high agreement, medium evidence) (Sections4.3.7, 4.5.7; Box8.1; Sections9.7.2, 10.3;
Box14.7).
Most climate-related migration and displacement observed currently takes place within countries (high confidence) (Sections4.3.7,
4.5.7, 5.12.2, 7.2.6). The climate hazards most commonly associated with displacement are tropical cyclones and flooding in most
regions, with droughts being an important driver in sub-Saharan Africa, parts of south Asia and South America (high confidence)
(Sections7.2.6.1, 9.7.2, 10.4.6.3, 11.4.1, 12.5.8.4, 13.8.1.3, 14.4.7.3). Currently, observed international migration associated with
climatic hazards is considerably smaller relative to internal migration and is most often observed as flowing between states that are
contiguous and have labour-migration agreements and/or longstanding cultural ties (high agreement, robust evidence) (Sections4.3.7,
4.5.7, 5.12.2, 7.2.6).
In many regions, the frequency and/or severity of floods, extreme storms and droughts is projected to increase in coming decades,
especially under high-emissions scenarios (WGI AR6 Chapter 12 (Ranasinghe etal. 2021)), raising future risk of displacement in the most
exposed areas (high confidence) (Section7.3.2.1). The additional impacts of climate change anticipated to generate future migration and
displacement include mean sea level rise that increases flooding and saltwater contamination of soil and/or groundwater in low-lying
coastal areas and small islands (high confidence) (Section7.3.2.1; Cross-Chapter BoxSLR in Chapter 3) and more frequent extreme heat
Ocello et al., 2015) but are also better able to migrate and with
greater agency once such a decision is made (Kubik and Maurel, 2016;
Koubi etal., 2016b; Riosmena etal., 2018; Adams and Kay, 2019). By
contrast, poor households with limited physical, social and financial
resources have less capacity to adapt in situ and are often limited in
their migration options (Nawrotzki and DeWaard, 2018; Suckall etal.,
2017; Zickgraf etal., 2016). Thus, when poorer households do migrate
after an extreme climate event, it is often in reaction to lost income or
livelihood and occurs with low voluntarity (Mallick etal., 2017; Bhatta
etal., 2015) and may perpetuate or amplify migrants’ socioeconomic
precarity and/or their exposure to environmental hazards (Natarajan
etal., 2019; see also Section8.3.1).
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Health, Wellbeing and the Changing Structure of Communities Chapter 7
events that threaten the habitability of urban centres in the tropics and arid/semiarid regions (medium confidence), although the causal
links between heat and migration are less clear (Section7.3.2.1).
There is growing evidence about the future prospects of immobile populations: groups and individuals that are unable or unwilling to
move away from areas highly exposed to climatic hazards (high confidence) (Sections4.6.9, 7.2.6.2; Box8.1; Box10.2). Involuntarily
immobile populations may be anticipated to require government interventions to continue living in exposed locations or to relocate
elsewhere (high agreement, medium evidence) (Box8.1). Managed retreat and organised relocations of people from hazardous areas
in recent years have proven to be politically and emotionally charged, socially disruptive and costly (high confidence) (Section7.4.5.4).
Climate-migration interactions and outcomes
FigureMIGRATE.1 in Chapter 7 presents a simplified framework for understanding how migration and displacement may emerge from
the interactions of climatic and non-climatic factors, based on the characteristic risk framework introduced in Chapter 1 (Section1.3).
Voluntary migration can be used by households when adapting to climate hazards, while less voluntary forms of migration and displacement
emerge when other forms of adaptation (referred to in FigureMIGRATE.1 in Chapter 7 as in situ adaptation) are inadequate. Migration
outcomes—expressed in FigureMIGRATE.1 in Chapter 7 as changes in future risks to the well-being of migrants, sending communities
and destination communities—are heavily influenced by the political, legal, cultural and socioeconomic conditions under which migration
occurs. Groups and individuals that are involuntarily immobile may find that their exposure, vulnerability and risk increase over time.
TableMIGRATE.1 in Chapter 7 summarises the range of potential migration outcomes that may emerge from this dynamic and indicates
specific sections in sectoral and regional chapters of the report that describe examples of each.
Climate-migration processes and outcomes
In SITU
Adaptation
Vulnerability
Exposure
Response
Hazard
Risk
Risk
decreases
Risk
increases
Climate Factors
Non-Climate Factors
S
u
c
c
e
s
s
f
u
l
i
n
S
i
t
u
A
d
a
p
t
a
t
i
o
n
Threshold(s)
MIGRATION OUTCOMES
See Table CCB 1
Immobility
FigureMIGRATE.1 | General interactions between climatic and non-climatic processes, adaptation, potential migration outcomes and implications
for future risk. Adapted from McLeman etal. (2021).
Cross-Chapter BoxMIGRATE (continued)
7
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Chapter 7 Health, Wellbeing and the Changing Structure of Communities
TableMIGRATE.1 |Typology of climate-related migration and examples in sectoral and regional chapters of AR6.
Type of climate-re-
lated migration
Characteristics
Recent or current
examples
Examples in the literature References in AR6 WGII
Temporary and/or
seasonal migration
Frequently used as a risk-reduction
strategy by rural households in
less-developed regions with highly
seasonal precipitation; includes
transhumance
Pastoralists in
sub-Saharan Africa;
seasonal farm workers in
south Asia; rural–urban
labour migration in
Central America
Afifi etal. (2016); Call etal.
(2017); Piguet etal. (2018);
Borderon etal. (2019); Cattaneo
etal. (2019); Hoffmann etal.
(2020); Lopez-i-Gelats etal.
(2015); Lu etal. (2016) Kaczan
and Orgill-Meyer (2020)
Sections5.5.1.1, 5.5.3.5;
Section7.2.6; Section8.2.1.3;
Section9.8.3; Box13.2
Indefinite or permanent
migration
Less common than temporary or seasonal
migration, particularly when the whole
household permanently relocates
Numerous examples in all
regions
See reviews listed in cell above
Section7.2.6; Section8.2.1.3;
Box10.2
Internal migration
Movements within state borders; most
common form of climate-related migration
Numerous examples in all
regions
See reviews listed in cell above
Section4.3.7; Sections5.5.4,
5.10.1.1; Section7.2.6;
Sections9.7.2, 9.11; Box9.8;
Sections10.3.3, 10.4.6.3,
Box10.2; Section11.4.1;
Section12.5.8.4; Section13.8.1.3;
Section14.4.7.3; Section15.3.4.6
International migration
Less common than internal migration;
most often occurs between contiguous
countries within the same region; often
undertaken for purpose of earning wages
to remit home
Cross-border migration
within south and
Southeast Asia,
sub-Saharan Africa
See reviews listed in cell above;
also Veronis etal. (2018);
McLeman (2019); Cattaneo and
G. (2016); Missirian and Schlenker
(2017); Schutte etal. (2021)
Sections4.3.7, 4.5.7;
Section5.12.2; Section7.2.6
Rural–urban or rural–
rural
Typically internal but may also flow
between contiguous states; may be
for temporary or indefinite periods;
migration may be undertaken by an
individual household member or the
entire household; may be followed by
remittances
Drought migration in
Mexico, east Africa and
south Asia
See reviews in the cell above;
also Adger etal. (2015); Gautier
etal. (2016); Nawrotzki etal.
(2017); Wiederkehr etal. (2018);
Robalino etal. (2015); Borderon
etal. (2019); Murray-Tortarolo and
Martnez (2021)
Section5.13.4; Section7.2.6;
Section6.2.4.3; Section8.2.1.3;
Section9.8.1.2; Section12.5.8.4;
Section14.4.7.1
Displacement
Households are forced to leave homes for
temporary or indefinite period; typically
occurs as a result of extreme events
and starts with seemingly temporary
evacuation; risk is expected to rise in most
regions due to sea level rise and changes
in associated coastal hazards
Tropical cyclones in the
Caribbean, Southeast Asia
and Bay of Bengal region
Islam and Shamsuddoha (2017);
Desai etal. (2021); see Internal
Displacement Monitoring Centre
annual reports for global statistics
Cross-Chapter BoxSLR in
Chapter 3; Section4.3.7; 4.5.7;
Cross-Chapter BoxMOVING PLATE
in Chapter 5; Section7.2.6.1;
Box8.1; Section9.7.2;
Section9.9.2; Section10.3;
Box14.7; Sections15.3.4.6;
CCP2.2.2
Planned and/or
organised resettlement
Initiated in areas where settlements
become permanently uninhabitable;
requires assistance from governments
and/or institutions; government-sponsored
sedentarisation of pastoral populations
Fiji, Carteret Islands,
Papua New Guinea, Gulf
of Mexico coast and
coastal Alaska, USA
Marino and Lazrus (2015);
Hino etal. (2017); McNamara
etal. (2018); McMichael and
Katonivualiku (2020); Tadgell etal.
(2017); Arnall (2014); Wilmsen
and Webber (2015)
Section4.6.9; Sections5.14.1,
5.14.2; Section7.4.4.4;
Section10.4.6; Section15.5.3;
CCP2.2.2; CCP6.3.2
Immobility
Adverse weather or climatic conditions
warrant moving, but households are
unable to relocate because of lack of
resources or choose to remain because
of strong social, economic or cultural
attachments to place
Examples in most regions
Adams (2016); Zickgraf (2018);
Nawrotzki and DeWaard (2018);
Farbotko etal. (2020)
Section4.6.9; Section7.2.6.2;
Box8.1; Box10.2
Policy implications
Future migration and displacement patterns in a changing climate will depend not only on the physical impacts of climate change, but
also on future policies and planning at all scales of governance (high confidence) (4.6.9, 5.14.1, 5.14.1.2, 7.3.2, 7.4.4, 8.2.1.3; Box8.1;
CCP6.3.2). Policy interventions can remove barriers to and expand the alternatives for safe, orderly and regular migration that allows
vulnerable people to adapt to climate change (high confidence) (Section7.2.6). With adequate policy support, migration in the context
Cross-Chapter BoxMIGRATE (continued)
7
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Health, Wellbeing and the Changing Structure of Communities Chapter 7
of climate change can result in synergies for both adaptation and development (Sections5.12.2, 7.4.4, 8.2.1.3). Migration governance at
local, national and international levels will influence the outcomes of climate-related migration for the migrants themselves as well as for
receiving and origin communities (Sections5.13.4, 7.4.4, 8.2.1.3). At the international level, a number of relevant policy initiatives and
agreements, including Global Compacts for Safe, Orderly and Regular Migration and for the protection of Refugees; the Warsaw
International Mechanism of the UNFCCC; the Sustainable Development Goals; the Sendai Framework for Disaster Risk Reduction; and the
Platform on Disaster Displacement, have already been established, merit continued pursuit and provide potential migration governance
pathways (Section7.4.4). Policy and planning decisions at regional, national and local scales that relate to housing, infrastructure, water
provisioning, schools and healthcare are relevant for successful integration of migrants into receiving communities (Sections5.5.4,
5.10.1.1, 5.12.2, 9.8.3). Policies and practices on movements of people across international borders are also relevant to climate-related
migration, with restrictions on movement having implications for the adaptive capacity of communities exposed to climate hazards
(Section7.4.4.2; Box8.1). Perceptions of migrants and the framing of policy discussions in receiving communities and nations are
important determinants of the future success of migration as an adaptive response to climate change (Section7.4.4.3) (high agreement,
medium evidence).
Reducing the future risk of large-scale population displacements, including those requiring active humanitarian interventions and
organised relocations of people, requires the international community to meet the requirements of the Paris Agreement and take further
action to control future warming (high confidence) (Cross-Chapter BoxSLR in Chapter 3; Section7.3.1; Box8.1). Current emissions
pathways lead to scenarios for the period between 2050 and 2100 in which hundreds of millions of people will be at risk of displacement
due to rising sea levels, floods, tropical cyclones, droughts, extreme heat, wildfires and other hazards, with land degradation exacerbating
these risks in many regions (Section7.3.2; IPCC 2019b; Cross-Chapter BoxSLR in Chapter 3). At high levels of warming, tipping points may
exist, particularly related to sea level rise, that, if crossed, would further increase the global population potentially at risk of displacement
(Ranasinghe etal. 2021). Populations in low-income countries and small-island states that have historically had low greenhouse gas
(GHG) emissions are at particular risk of involuntary migration and displacement due to climate change, reinforcing the urgency for
industrialised countries to continue lowering GHG emissions, to support adaptive capacity-building initiatives under the UNFCCC and to
meet objectives expressed in the Global Compacts regarding safe, orderly and regular migration and the support and accommodation of
displaced people (Sections4.3.7, 4.5.7, 5.12.2, 7.4.5.5, 8.4.2; Box8.1; Cross-Chapter BoxSLR in Chapter 3).
Cross-Chapter BoxMIGRATE (continued)
Climate-related migration originates most often in rural areas in
low- and middle-income countries, with migrant destinations usually
being other rural areas or urban centres within their home countries
(i.e., internal migration) (medium confidence). Rural livelihoods and
incomes based on farming, livestock rearing and/or natural resource
collection are inherently sensitive to climate variability and change,
creating greater potential for migration as a response (Bohra-Mishra
et al., 2017; Viswanathan and Kumar, 2015). Drought events have
been associated with periods of higher rural to urban migration
within Mexico (Chort and de la Rupelle, 2016; Leyk et al., 2017;
Nawrotzki et al., 2017; Murray-Tortarolo and Martnez, 2021) and
Senegal (Nawrotzki and Bakhtsiyarava, 2017). Extreme temperatures
are associated with higher rates of temporary rural out-migration in
South Africa and in Bangladesh (Mastrorillo etal., 2016; Call etal.,
2017). In rural Tanzania, weather-related shocks to crop production
have been observed to increase the likelihood of migration but
typically only for households in the middle of community wealth
distribution (Kubik and Maurel, 2016). Weather-related losses in rice
production have been associated with small-percentage increases
in internal migration in India (Viswanathan and Kumar, 2015) and
the Philippines (Bohra-Mishra etal., 2017). In east Africa, temporary
rural–urban labour migration does not show a strong response to
climatic drivers (Mueller etal., 2020). There is limited literature on
mobility as adaptation in urban populations, with the focus being on
resettlement of flood-prone informal settlements within cities (Kita,
2017; Tadgell etal., 2017).
Most documented examples of international climate-related migration
are intra-regional movements of people between countries with shared
borders (high agreement, medium evidence). Systematic reviews find
few documented examples of long-distance, inter-regional migration
driven by climate events (Veronis et al., 2018; Kaczan and Orgill-
Meyer, 2020; Hoffmann et al., 2020). One macro-economic analysis
found a correlation between migrant flows from low- to high-income
countries and adverse climatic events in the source country (Coniglio
and Pesce, 2015). Another study found that high heat stimulates higher
rates of international migration from middle-income countries but
typically not from low-income countries (Cattaneo and Peri., 2016),
while other studies found international climate-related migration
originates primarily from agriculture-dependent countries (Cai etal.,
2016; Nawrotzki and Bakhtsiyarava, 2017). Small-sample studies of
migrants to Canada from Bangladesh, Haiti and sub-Saharan Africa
suggest environmental factors in the source country can be a primary
or secondary motivation for some migrants within larger flows of
economic and family-reunification migrants (Veronis and McLeman,
2014; Mezdour et al., 2015; McLeman et al., 2017). Research on
the links between climate hazards and international movements of
refugees and/or asylum seekers shows differing results. One study
found that asylum applications in Europe increase during climate
fluctuations due to interactions with conflict (Missirian and Schlenker,
2017), and another found links between heat, drought, conflict and
asylum-seeking migration originating in the Middle East between
2011 and 2015 (Abel et al., 2019). Other studies have found that
7
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Chapter 7 Health, Wellbeing and the Changing Structure of Communities
Average annual weather-related displacements, 2010–2020
Wet mass movement
Mass movement
Extreme temperatures
Drought
Wildfire
Storm
Flood
C. & S.
America
Small
Islands
Europe Australasia
Millions
of people
displaced
Weather-related hazards
Expanded inset
2
4
6
8
10
12
14
16
18
Asia Africa
North
America
Central
and South
America
Small
Islands
Europe Australasia
0
0.1
0
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
Figure7.7 | Average number of people displaced annually by selected weather-related events from 2010 to 2020 by region. See text for important notes
regarding data collection and trends. Source statistics provided by the Internal Displacement Monitoring Centre (https://www.internal-displacement.org/).
asylum claims in Europe correspond minimally with climatic hazards
in source countries (Schutte etal., 2021), with choices in baseline data,
timeframes for analysis and methodological approaches potentially
explaining the inconsistent results across studies (Boas etal., 2019).
Media reports and other studies in recent years suggest that climate
change has driven large numbers of migrants to the US from Central
America and to Europe from the Middle East and Africa, but empirical
studies were not identified for this assessment.
7.2.6.1 Relative Importance of Specific Climatic Drivers of
Migration and Displacement
Reliable global estimates of voluntary climate-related migration
within and between countries are not available due to a general
absence of data of this specific nature, with existing national and
global datasets often lacking information on migration causation or
motivation. Better data are available for involuntary displacements
within countries for reasons associated with weather-related hazards.
Data collected annually since 2008 on internal displacements
attributed to extreme weather events by the IDMC indicate that
extreme storms and floods are the two most significant weather-
related drivers of population displacements globally. Because of
improvements in collection sources and methods since it first began
reporting data in 2008, upward trends since that year in the total
reported annual number of people displaced should be treated
cautiously. However, it is reasonable to conclude that the average
annual rate currently exceeds 20 million people globally, with
considerable interannual variation due to the frequency and severity
of extreme events in heavily populated areas. Regional distribution
of displacement events has been consistent throughout the IDMC
data collection period (high confidence), with displacement events
occurring most often in East, Southeast and south Asia; sub-Saharan
Africa; the USA; and the Caribbean region (Figure 7.7). Relative
to their absolute population size, small island states experience a
disproportionate risk of climate-related population displacements
(Desai etal., 2021) (high confidence).
Tropical cyclones and extreme storms are a particularly significant
displacement risk in East and Southeast Asia, the Caribbean region,
the Bay of Bengal region and southeast Africa (IDMC 2020) (high
confidence). The scale of immediate displacement from any given
storm and potential for post-event migration depend heavily on the
extent of damage to housing and livelihood assets and the responsive
capacity of governments and humanitarian relief agencies (Saha,
2016; Islam et al., 2018; Mahajan, 2020; Spencer and Urquhart,
2018). In Bangladesh, the rural poor are most often displaced, with
initial increases in short-term, labour-seeking migration followed by
more permanent migration by some groups (Saha, 2016; Islam and
Hasan, 2016; Islam and Shamsuddoha, 2017). Past hurricanes in the
Caribbean basin have generated internal and inter-state migration
within the region, typically along pre-existing social networks,
and to the USA (Loebach, 2016; Chort and de la Rupelle, 2016). In
2017, Hurricanes Irma and Maria caused widespread damage to
infrastructure and health services, and a slow recovery response by
authorities was followed by the migration of tens of thousands of
Puerto Ricans to Florida and New York (Zorrilla, 2017; Echenique and
Melgar, 2018). In the US, coastal counties experience increased out-
migration after hurricanes that flows along existing social networks
(Hauer, 2017), with post-disaster reconstruction employment
opportunities potentially attracting new labour migrants to affected
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Health, Wellbeing and the Changing Structure of Communities Chapter 7
areas (Ouattara and Strobl, 2014; Curtis etal., 2015; DeWaard etal.,
2016; Fussell etal., 2018).
Riverine flood displacement can lead to increases or decreases in
temporary or short-distance migration flows, depending on the local
context (medium confidence) (Robalino et al., 2015; Ocello et al.,
2015; Afifi etal., 2016; Koubi etal., 2016b). Floods are a particularly
important driver of displacement in river valleys and deltas in Asia and
Africa, although large flood-related displacements have been recorded
by the IDMC in all regions. In Africa, populations exposed to low flood
risks, as compared with other regions, are observed to have a greater
vulnerability to displacement due to limited economic resources and
adaptive capacity (Kakinuma etal., 2020). In areas where flooding is
especially frequent, in situ adaptations may be more common, and
out-migration may temporarily decline after a flood (Afifi etal., 2016;
Chen etal., 2017; Call etal., 2017). Rates of indefinite or permanent
migration tend not to change following riverine floods unless damage
to homes and livelihood assets is especially severe and widespread,
with household perceptions of short- and longer-term risks playing an
important role (Koubi etal., 2016a).
Displacements due to droughts, extreme heat and associated impacts on
food and water security are most frequent in east Africa and, to a lesser
extent, south Asia and west and southern Africa (IDMC, 2020). Since
droughts unfold progressively and typically do not cause permanent
damage to housing or livelihood assets, there is greater opportunity for
government and non-governmental organisation (NGO) interventions
and greater use of in situ adaptation options (Koubi et al., 2016b;
Koubi etal., 2016a; Cattaneo etal., 2019). Drought-related population
movements are most common in dryland rural areas of low-income
countries and occur after a threshold is crossed and in situ adaptation
options are exhausted (Gautier etal., 2016; Wiederkehr etal., 2018;
McLeman, 2017). Observed population movements may occur for an
extended period after the event; one study of Mexican data found this
lag to be up to 36months (Nawrotzki etal., 2017). The most common
response to drought is an increase in short-distance, rural–urban
migration (medium confidence), with examples being documented
in Bangladesh, Ethiopia, Pakistan, sub-Saharan Africa, Latin America
and Brazil (Neumann and Hermans, 2015; Gautier etal., 2016; Gautier
etal., 2016; Mastrorillo etal., 2016; Baez etal., 2017; Call etal., 2017;
Nawrotzki etal., 2017; Jessoe etal., 2018; Carrico and Donato, 2019;
Hermans and Garbe, 2019).
Few assessable studies were identified that examine links between
wildfires and migration. Wildfire events are often associated with
urgent evacuations and temporary relocations, which place significant
stress on receiving communities (Spearing and Faust., 2020), but
research in the USA suggests fires have only a modest influence on
future migration patterns in exposed areas (Winkler and Rouleau.,
2021). More research, particularly in other regions, is needed.
7.2.6.2 Immobility and Resettlement in the Context of Climatic
Risks
Immobility in the context of climatic risks can reflect vulnerability and
lack of agency (an inability to migrate), but can also be a deliberate
choice (high confidence). Research since AR5 shows that immobility
is best described as a continuum from people who are financially or
physically unable to move away from hazards (involuntary immobility)
to people who choose not to move (voluntary immobility) because
of strong attachments to place, culture and people (Nawrotzki and
DeWaard, 2018; Adams, 2016; Farbotko and McMichael, 2019; Zickgraf,
2019; Neef etal., 2018; Suckall etal., 2017; Ayeb-Karlsson etal., 2018;
Zickgraf, 2018; Mallick and Schanze, 2020). Involuntary immobility is
associated with individuals and households with low adaptive capacity
and high exposure to hazard, and can exacerbate inequality and future
Box7.4 | Gender Dimensions of Climate-Related Migration
Migration decision-making and outcomes—in both general terms and in response to climatic risks—are strongly mediated by gender,
social context, power dynamics and human capital (Bhagat, 2017; Singh and Basu, 2020; Rao etal., 2019a; Ravera etal., 2016). Women
tend to suffer disproportionately from the negative impacts of extreme climate events for reasons ranging from caregiving responsibilities
to lack of control over household resources to cultural norms for attire (Belay etal., 2017; Jost etal., 2016). In many cultures, migrants
are most often able-bodied, young men (Call etal., 2017; Heaney and Winter, 2016). Womenwait longer to migrate because of higher
social costs and risks (Evertsen and Van Der Geest, 2019) and barriers such as social structures, cultural practices, lack of education and
reproductive roles (Belay etal., 2017; Afriyie etal., 2018; Evertsen and Van Der Geest, 2019).
Research critiques the tendency to portray women as victims of climate hazards rather than recognising differences between women and
the potential for women to use their agency and informal networks to negotiate their situations (Eriksen etal., 2015; Ngigi etal., 2017;
Pollard etal., 2015; Rao etal., 2019b; Ravera etal., 2016). Migration can change household composition and structure, which in turn
affects the adaptive capacity and choices of those who do not move (Rao etal., 2019a; Rao etal., 2019b; Singh, 2019). For example, when
only male household members move, the remaining members of the now female-headed household must take on greater workloads
(Goodrich etal., 2019; Rao etal., 2019b; Rigg and Salamanca, 2015), leading to increased workload and greater vulnerability for those
left behind (Arora etal., 2017; Bhagat, 2017; Flatø etal., 2017; Lawson etal., 2019). It can, however, also increase women’s economic
freedom and decision-making capacity, enhance their agency (Djoudi etal., 2016; Rao, 2019) and alter the gendered division of paid
work, care and intra-household relations (Rigg etal., 2018; Singh and Basu, 2020), a process that may reduce household vulnerability to
extreme climate events (Banerjee etal., 2019b).
7
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Chapter 7 Health, Wellbeing and the Changing Structure of Communities
vulnerability to climate change (Sheller, 2018), including through
impacts on health (Schwerdtle et al., 2018). Voluntary immobility
represents an assertion of the importance of culture, livelihoods and
people to well-being, and is of particular relevance for Indigenous
Peoples (Suliman etal., 2019).
Planned relocations by governments of settlements and populations
exposed to climatic hazards are not presently commonplace,
although the need is expected to grow in coming decades (Hino
et al 2017). Examples include relocations of coastal settlements
exposed to storm and erosion hazards as well as smaller numbers
of cases of flood-prone settlements in river valleys; these examples
suggest that organised relocations are expensive, contentious, create
multiple challenges for governments and generate short- and longer-
term disruptions for the people involved (high agreement, medium
evidence) (Ajibade etal., 2020; Henrique and Tschakert, 2020; Desai
etal., 2021).
Examples of relocations of small indigenous communities in coastal
Alaska and villages in the Solomon Islands and Fiji suggest that
relocated people experience significant financial and emotional distress
as cultural and spiritual bonds to place and livelihoods are disrupted
(Albert etal., 2018; Neef etal., 2018; McMichael and Katonivualiku,
2020; McMichael and Katonivualiku, 2020; McMichael et al., 2021;
Piggott-McKellar et al., 2019; Bertana, 2020). Voluntary relocation
programmes offered by US state governments in communities damaged
by Hurricane Sandy in 2012 have been subject to multiple studies, and
these show longer-term economic outcomes, social connections and
mental well-being vary for a range of reasons unrelated to the impacts
of the hazard event itself (Bukvic and Owen, 2017; Binder etal., 2019;
Koslov and Merdjanoff, 2021).
7.2.6.3 Connections Between Climate-Related Migration and
Health
The number of assessable peer-reviewed studies that make connections
between climate-related migration and health and well-being is small.
The health outcomes of migrants generally, and of climate-migrants
in particular, vary according to geographical context, country and the
particular circumstances of migration or immobility (Hunter and Simon,
2017; Hunter et al., 2021; Schwerdtle et al., 2020). Such linkages are
‘multi-directional’, with studies suggesting that healthy individuals
may be more likely to migrate internationally in search of economic
opportunities than people in poorer health, except during adverse
climatic conditions when migration rates may change across all groups,
and that migrants may have different long-term health outcomes than
people born in destination areas, potentially displaying a range of positive
and negative health outcomes compared to non-migrants (Kennedy
etal., 2015; Dodd etal., 2017; Hunter and Simon, 2017; Riosmena etal.,
2017). Refugees and other involuntary migrants often experience higher
exposure to disease and malnutrition, adverse indirect health effects of
changes in diet or activity and increased rates of mental health concerns.
These latter may be attributable to a sense of loss or fear (Schwerdtle
etal., 2018; Torres and Casey, 2017) as well as due to the interruption
of healthcare; occupational injuries; sleep deprivation; non-hygienic
lodgings and insufficient sanitary facilities; heightened exposure to
vector- and WBDs; vulnerability to psychosocial, sexual and reproductive
issues; behavioural disorders; substance abuse; and violence (Farhat etal.,
2018; Wickramage et al., 2018) (high confidence). Linkages between
climate migration and the spread of infectious disease are bidirectional;
migrants may be exposed to diseases at the destination to which they
have lower immunity than the host community; in other cases, migrants
could introduce diseases to the receiving community (McMichael, 2015).
Thus, receiving areas may have to pay greater attention to building
migrant sensitive health systems and services (Hunter and Simon, 2017).
The risk of migration leading to disease transmission is exacerbated by
weak governance and lack of policy to support public health measures
and access to medicines (Pottie etal., 2015).
7.2.7 Observed Impacts of Climate on Conflict
7.2.7.1 Introduction
In AR5, conflict was addressed in WGII Chapter 12 on human security.
The chapter concluded that some of the factors that increase the risk of
violent conflict within states are sensitive to climate change (medium
evidence, medium agreement), that people living in places affected by
violent conflict are particularly vulnerable to climate change (medium
confidence) and that climate change will lead to new challenges to
states and will increasingly shape both conditions of security and
national security policies (medium evidence, medium agreement). AR5
characterised a major debate within the field as: authors supporting
an association between climate anomalies and conflict that can be
extrapolated into the future (e.g., Hsiang etal. (2013); Hsiang and
Marshall (2014); Burke etal. (2015a)) and authors arguing that these
associations are not universal and break down when contextual, scale
and political factors are introduced (e.g., Buhaug etal. (2014); Buhaug
(2016)).
Consistent with AR5 findings, there continues to be little observed
evidence that climatic variability or change cause violent inter-state
conflict. In intra-state settings, climate change has been associated
with the onset of conflict, civil unrest or riots in urban settings (high
agreement, medium evidence) (Ide (2020), and changes in the duration
and severity of existing violent conflicts (Koubi, 2019). Climate change
is conceptualised as one of many factors that interact to raise tensions
(Boas and Rothe, 2016) through diverse causal mechanisms (Mach
etal., 2019; Ide etal., 2020) and as part of the peace-vulnerability-
development nexus (Barnett, 2019; Abrahams, 2020; Buhaug and von
Uexkull, 2021). New areas of the literature assessed in this report
include the security implications of responses to climate change, the
gendered dynamics of conflict and exposure to violence under climate
change and civil unrest in urban settings. The impact of violent conflict
on vulnerability is not addressed in this chapter but does arise in
other chapters (Sections 8.3.2.3, 17.2.2.2). Other chapters address
non-violent conflict over changing availability and distribution of
resources, for example, competing land uses and fish stocks migrating
to different territories (Sections 5.8.2.3; 5.8.3, 5.9.3, 5.13, 9.8.1.1,
9.8.5.1). A commonly used definition of armed conflict is conflicts
involving greater than 25 battle-related deaths in a year; this number
represents the Uppsala Conflict Data Program threshold for inclusion
in their database, a core resource in this field.
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Health, Wellbeing and the Changing Structure of Communities Chapter 7
Climatic conditions have affected armed conflict within countries, but
their influence has been small compared to socioeconomic, political
and cultural factors (Mach et al., 2019) (high agreement, medium
evidence). Inter-group inequality, and consequent relative deprivation
can lead to conflict and the negative impacts of climate change
lower the opportunity cost of involvement in conflict (Buhaug etal.,
2020; Vestby, 2019). Potential pathways linking climate and conflict
include direct impacts on physiology from heat or resource scarcity;
indirect impacts of climatic variability on economic output, agricultural
incomes, higher food prices and increasing migration flows; and the
unintended effects of climate mitigation and adaptation policies (Koubi,
2019; Busby, 2018; Sawas etal., 2018). Relative deprivation, political
exclusion and ethnic fractionalisation and ethnic grievances are other
key variables (Schleussner etal., 2016; Theisen, 2017). Research shows
that factors such as land tenure and competing land uses interacting
with market-driven pressures and existing ethnic divisions produce
conflict over land resources rather than a scarcity of natural resources
caused by climate impacts such as drought (high agreement, medium
evidence) (Theisen, 2017; Balestri and Maggioni, 2017; Kuusaana and
Bukari, 2015; Box8.3).
7.2.7.2 Impacts of Climate Change and Violent Conflict
Positive temperature anomalies and average increases in temperature
over time have been associated with collective violent conflict in certain
settings (medium agreement, low evidence). Helman and Zaitchik
(2020) find statistical associations between temperature and violent
conflict in Africa and the Middle East that are stronger in warmer places
and identify seasonal temperature effects on violence. However, they
are unable to detect the impact of regional temperature increases on
violence. For Africa, Van Weezel (2019) found associations between
average increases in temperature and conflict risk. Caruso etal. (2016)
found an association between rises in minimum temperature and
violence through the impact of temperature on rice yields (Box9.4).
However, the associations between temperature and violence are
weak compared to those with political and social factors (e.g., Owain
and Maslin (2018)) and research focuses on areas where conflict is
already present and, as such, is sensitive to selection bias (Adams etal.,
2018). There is a body of literature that finds statistical associations
between temperature anomalies and inter-personal violence, crime
and aggression in the Global North, predominantly in the USA (e.g.,
Ranson (2014); Mares and Moffett (2019); Tiihonen et al. (2017);
Parks etal. (2020); Section14.4.8). However, authors have cautioned
against extrapolating seasonal associations into long-term trends and
against focusing on individual crimes rather than wider social injustices
associated with climate change and its impacts (Lynch etal., 2020).
Variation in availability of water has been associated with international
political tension and intra-national collective violence (low agreement,
medium evidence). Drought conditions have been associated with
violence due to impacts on income from agriculture and water and
food security, with studies focusing predominantly on sub-Saharan
Africa and the Middle East (Ide and Frohlich, 2015; De Juan, 2015; Von
Uexkull etal., 2016; Waha etal., 2017; Abbott etal., 2017; D’Odorico
etal., 2018). A small set of published studies has argued inconclusively
over the role of drought in causing the Syrian civil war (Gleick, 2014;
Kelley etal., 2015; Selby etal., 2017; 16.2.3.9). In general, research
stresses the underlying economic, social and political drivers of
conflict. For example, research on conflict in the Lake Chad region
has demonstrated that the lake drying was only one of many factors
including lack of development and infrastructure (Okpara etal., 2016;
Nagarajan etal., 2018; Tayimlong, 2020). Fewer studies examine the
relationship between flooding (excess water) and violence and often
rely on migration as the causal factor (see below). However, some
studies have shown an association between flooding and civil unrest
(Ide etal., 2020; Section4.3.6; Section12.5.3; Box9.4).
Extreme weather events can be associated with increased conflict risk
(low agreement, medium evidence). There is the potential for extreme
weather events and disasters to cause political instability and increase
the risk of violent conflict, although not conclusively (Brzoska, 2018).
Post-disaster settings can be used to intensify state repression (Wood
and Wright, 2016) and to alter insurgent groups’ behaviour (Walch,
2018). Different stakeholders use disasters to establish new narratives
and alter public opinion (Venugopal and Yasir, 2017). Some research
has demonstrated how post-disaster activities have had positive
impacts on the social contract between people and the state, reducing
the risk of conflict by strengthening relations between government and
citizens and strengthening the citizenship of marginalised communities
(Siddiqi, 2018; Pelling and Dill, 2010; Siddiqi, 2019). However, post-
disaster and disaster risk-related activities themselves have limited
capacity to support diplomatic efforts to build peace (Kelman etal.,
2018).
7.2.7.3 Causal Pathways Between Climate Change Impacts and
Violent Conflict
Increases in food prices due to reduced agricultural production and
global food price shocks are associated with conflict risk and represent
a key pathway linking climate variability and conflict (medium
confidence). Increases in food prices are associated with civil unrest
in urban areas among populations unable to afford or produce their
own food and in rural populations due to changes in availability of
agricultural employment with shifting commodity prices (Martin-
Shields and Stojetz, 2019). Under such conditions, locally specific
grievances, hunger and social inequalities can initiate or exacerbate
conflicts. Food price volatility in general is not associated with violence,
but sudden food price hikes have been linked to civil unrest in some
circumstances (Bellemare, 2015; McGuirk and Burke, 2020; Winne and
Peersman, 2019). In urban settings in Kenya, Koren etal. (2021) found
an association between food and water insecurity that is mutually
reinforcing and associated with social unrest (although insecurity in
either food or water on its own was not). Analysing the global food
riots in 2007/2008 and 2011, Heslin (2021) stresses the role of local
politics and pre-existing grievances in determining whether people
mobilise around food insecurity (Chapter 5).
Climate-related internal migration has been associated with the
experience of violence by migrants, the prolongation of conflicts in migrant
receiving areas and civil unrest in urban areas (medium agreement, low
evidence). Research points to the potential for conflict to serve as an
intervening factor between climate and migration. However, the nature
of the relationship is diverse and context specific. For example, displaced
people and migrants may be associated with heightened social tensions
7
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Chapter 7 Health, Wellbeing and the Changing Structure of Communities
in receiving areas through mechanisms such as ecological degradation,
reduced access to services and a disturbed demographic balance in the
host area (Rüegger and Bohnet, 2020). Ghimire etal. (2015) observed
that an influx of flood-displaced people prolonged conflict by causing a
lack of access to services for some of the host population and feelings of
grievance. Further, migration from drought-stricken areas to local urban
centres has been used to suggest a climate trigger for the Syrian conflict
(e.g., Ash and Obradovich (2020)). However, this link has been strongly
contested by research that contextualises the drought in wider political
economic approaches and existing migration patterns (De Châtel, 2014;
Fröhlich, 2016; Selby, 2019; 16.2.3.9).
There is some evidence of an association between climate-related
rural-to-urban migration and the risk of civil unrest (medium
agreement, low evidence). Petrova (2021) found that while migration
in general was associated with increased protests in urban receiving
areas, the relationship did not hold for hazard-related migration. In
other settings, the association of civil unrest with in-migration was
found to depend on the political alignment of the host state with the
capital (Bhavnani and Lacina, 2015), previous experience of extreme
climate hazards (Koubi et al., 2021) and previous experience of
violence among migrants (Linke etal., 2018). Climate-related migrants
have reported higher levels of perception and experience of violence
in their destination (Linke etal., 2018; Koubi etal., 2018). There has
been no association established between international migration and
conflict. The literature highlights how unjust racial logics may generate
spurious links between climate migration and security (Fröhlich, 2016;
Telford, 2018).
7.2.7.4 Gendered Dimensions of Climate-Related Conflict
Structural inequalities play out at an individual level to create gendered
experiences of violence (high agreement, medium evidence). Violent
conflict is experienced differently by men and women because of
gender norms that already exist in society and shape vulnerabilities.
For example, conflict deepens gendered vulnerabilities to climate
change related to unequal access to land and livelihood opportunities
(Chandra et al., 2017). Motivations for inter-group violence may
be influenced by constructions of masculinity, for example the
responsibility to secure their family’s survival or pay dowries
(Myrttinen etal., 2017), and gendered roles may incentivise young
men to protest or to join non-state armed groups during periods of
adverse climate (Myrttinen etal., 2015; Myrttinen etal., 2017; Anwar
etal., 2019; Hendrix and Haggard, 2015; Koren and Bagozzi, 2017).
Research has found a positive correlation between crop failures and
suicides by male farmers who could not adapt their livelihoods to
rising temperatures (Bryant and Garnham 2015; Kennedy and King,
2014; Carleton, 2017).
Extreme weather and climate impacts are associated with increased
violence against women, girls and vulnerable groups (high agreement,
medium evidence). During and after extreme weather events, women,
girls and LGBTQI people are at increased risk of domestic violence,
harassment, sexual violence and trafficking (Le Masson etal., 2019;
Nguyen, 2019;Myrttinen etal., 2015; Chindarkar, 2012). For example,
early marriage is used as a coping strategy for managing the effects
of extreme weather events (Ahmed et al., 2019) and women are
exposed to increase risk of harassment and sexual assault as scarcity
and gender-based roles cause them to walk longer distances to fetch
water and fuel (Le Masson etal., 2019). Within the household, violent
backlash or heightened tensions may arise from changing gender
norms as men migrate to find work in post-disaster settings (Stork
etal., 2015) and men’s use of negative coping mechanisms, such as
alcoholism, when unable to meet norms of providing for the household
(Anwar et al., 2019; Stork et al., 2015). Rates of intimate partner
violence have been found to increase with higher temperatures (Sanz-
Barbero etal., 2018).
7.2.7.5 Observed Impacts on Non-violent Conflict and Geopolitics
Climate adaptation and mitigation projects implemented without
taking local interests and dynamics into account have the potential
to cause conflict (high agreement, medium evidence). Reforestation
or forest management programmes driven by reducing emissions
through deforestation, land zoning and managed retreat due to sea
level rise have been identified as having the potential to cause friction
and conflict within and between groups and communities (de la Vega-
Leinert etal., 2018; Froese and Schilling, 2019). Conflict may arise
when there is resistance to a proposed project, where interventions
favour one group over another, or when projects undermine
livelihoods or displace populations (e.g., Nightingale (2017); Sovacool
et al. (2015); Sovacool (2018); Corbera (2017); Hunsberger (2018);
Sections 4.6.8, 5.13.4, 14.4.7.3). In addition to conflict generated
by the poor implementation of land-based climate mitigation and
adaptation projects, Gilmore and Buhaug (2021) highlight the links
between climate policy and conflict through the potential effects of
unequal distribution of economic burdens and fossil fuel markets on
economic growth. There is a small literature that draws attention
to the potential security of nuclear proliferation, if nuclear energy
is increasingly employed as a low-carbon energy source (e.g.,
Parthemore etal. (2018); Bunn, (2019)).
Economic and social changes due to changes in sea ice extent in the
Arctic are anticipated to be managed as part of existing governance
structures (high agreement, medium evidence). The opening-up of the
Arctic and associated geopolitical manoeuvring for access to shipping
routes and sub-sea hydrocarbons is often highlighted as a potential
source of climate conflict (e.g., Koivurova (2009); Åtland (2013);
Tamnes and Offerdal (2014)). Research assessed in AR5 focused
on the potential for resource wars and Arctic land grabs. However,
research since AR5 is less sensationalist in its approach to Arctic
security, focusing instead on the practicalities of polycentric Arctic
governance under climate change, the economic impacts of climate
change, protecting the human security of Arctic populations whose
autonomy is at risk (Heininen and Exner-Pirot, 2020), understanding
how different regions (e.g., the EU) are positioning themselves more
prominently in the Arctic space (Raspotnik and Østhagen, 2019) and
Arctic Indigenous Peoples’ understanding of security (Hossain, 2016;
Chapter 3; Chapter 14; CCP6).
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Health, Wellbeing and the Changing Structure of Communities Chapter 7
7.3 Projected Future Risks under Climate
Change
7.3.1 Projected Future Risks for Health and Well-Being
7.3.1.1 Global Impacts
Climate change is expected to significantly increase the health risks
resulting from a range of climate-sensitive diseases and conditions,
with the scale of impacts depending on emissions and adaptation
pathways in coming decades (very high confidence). Sections7.3.1.2
to 7.3.1.11 assess the available studies on future projections for risks
associated with specific climate-sensitive diseases and conditions
previously described in Section7.2.1. In the case of diabetes, cancer,
injuries, mosquito-borne diseases other than dengue and malaria,
rodent-borne diseases and most mental illnesses, insufficient literature
was found to allow for assessment. Adaptation pathways and options
for managing such risks are detailed in Section7.4.
Even in the absence of further warming beyond current levels, the
proportion of the overall global deaths caused by climate-sensitive
diseases and conditions would increase marginally by mid-century
Heat in elderly people Diarrhoeal disease in children under 15 years Malaria Dengue Undernutrition (stunting)
Total deaths
2030 2050
2030 2050
Australasia &
Oceania
Southern Africa
Central Latin America
& Carribean
North Amercia
South-east Asia
92809
66114
South Asia
Cause of death
6102
2992
7769
4083
Andean
Latin
America
Southern Latin America
Tropical Latin America
Eastern Africa
Dengue
Malaria
Undernutrition
Diarrhoeal
Heat
Asia Pacific, high income
West Africa
Africa and Middle East total
Asia total
Europe total
127418
162383
Australasia &
Oceania total
North America total
Central &
South Amercia total
351
172
Central Asia
East Asia
Central
Africa
Adapted from source: World Health Organization. 2014. Quantitative risk assessment of the effects of climate change on selected causes of death, 2030s and 2050s.
10473
5485
Europe
North
Africa &
Middle
East
Figure7.8 | Projected additional annual deaths attributable to climate change in 2030 and 2050 compared to 1961–1990 (WHO, 2014).
7
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Chapter 7 Health, Wellbeing and the Changing Structure of Communities
(high confidence). Two global projections of climate change health
impacts have been conducted since AR5. The first focused on cause-
specific mortality for eight exposures for 2030 and 2050 for a mid-
range emissions scenario (A1b) and three scenarios of economic growth
(WHO, 2014). The study estimated that the climate change projected
to occur by 2050 (compared to 1961–1990) could result in an excess
of approximately 250,000 deaths yr
–1
, dominated by increases in
deaths due to heat (94,000, mainly in Asia and high-income countries),
childhood undernutrition (85,000, mainly in Africa but also in Asia),
malaria (33,000, mainly in Africa) and diarrhoeal disease (33,000, mainly
in Africa and Asia). Overall, more than half of this excess mortality is
projected for Africa. Near-term projections (for 2030) are predominantly
for childhood undernutrition (95,200 out of 241,000 total excess deaths)
(Figure 7.8). The second study (Carleton et al. 2020) focused on all-
cause mortality associated with warming under both a high emissions
scenario (RCP8.5) and a middle emissions scenario (RCP4.5). The
analyses created a metric of death equivalents that accounted for hot
and cold temperature-related mortality and the costs of individual level
adaptation; no acclimatization or community-level adaptation, such as
early warning systems, were incorporated. Average annual temperature-
mortality-income per capita relationships estimated from pooled data
from 40 predominantly middle- and high-income countries (38% of the
world population) were applied worldwide. Under the high emissions
scenario, climate change was projected to result in approximately 85
deaths equivalents per 100,000 population.
Temperature increases are projected to exceed critical risk thresholds
for six key climate-sensitive health outcomes, highlighting the criticality
of building adaptive capacity in health systems and in other sectors
that influence health and well-being (high confidence). Recently
reported research illustrates the temperature thresholds underthree
adaptation scenarios describing the effectiveness of health systems
to manage additional risks from climate change for heat-related
morbidity and mortality; ozone-related mortality; malaria incidence
rates; incidence rates of Dengue and other diseases spread byAedes
sp. mosquitos; Lyme disease; and West Nile fever(Ebi etal., 2021a). As
shown in Figure7.9,these adaptation scenarios significantly alterthe
warming thresholds at which risks accelerate, with the proactive
adaptation scenario, a scenario that emphasises international
cooperation towards achieving sustainable development, having
the greatest potential to avoid significant increases in risks under
all but the highest levels of warming. The incomplete adaptation
scenariodescribes a world with moderate challenges to adaptation
and mitigation.The limited adaptation scenariodescribes a world with
high challenges to adaptation and mitigation. In the figure, transitions
are based on the peer-reviewed literature projecting risks for each of
the health outcomes. Projections for time intervals were changed to
temperature increase above pre-industriallevels based on the climate
models and scenarios used in the projections.The assessed projections
were based on a range of scenarios,including SRES, CMIP5, and ISIMIP,
and, in some cases, demographic trends.The black dots are levels of
Climate sensitive health outcomes under three adaptation scenarios
Scenario narratives
Limited adaptation: Failure to proactively adapt; low investment in health systems.
Incomplete adaptation: Incomplete adaptation planning; moderate investment in health systems.
Proactive adaptation: Proactive adaptive management; higher investment in health systems
Historical average
temperature increase
in 2011–2020 was
1.09°C (dashed line)
range 0.95–1.20°C
Confidence level
assigned to
transition
range
Risk/impact
Low Very high
Very high
High
Moderate
Undetectable
••
••
••••
Transition range
* Mortality projections
include demographic
trends but do not
include future efforts
to improve air quality
that reduce ozone
concentrations.
0
2
3
4
1.5
1
Global surface temperature change (°C)
Limited
adaptation
Heat-related morbidity
and mortality
Proactive
adaptation
Incomplete
adaptation
••••••••
••••
•••••
Limited
adaptation
Ozone-related mortality *
Proactive
adaptation
Incomplete
adaptation
••••••
••••
••••••
Limited
adaptation
Malaria
Incomplete
adaptation
Proactive
adaptation
••••••
••••••
••••
0
2
3
4
1.5
1
Global surface temperature change (°C)
•••• •• ••
•••• ••
••••
Lyme disease
Limited
adaptation
Incomplete
adaptation
Proactive
adaptation
••• ••
•• ••
••
West Nile fever
Limited
adaptation
Incomplete
adaptation
Proactive
adaptation
Limited
adaptation
Dengue and other diseases carried
by species of Aedes mosquitoes
Proactive
adaptation
Incomplete
adaptation
••••••••
••••
•••••
Figure7.9 | Climate-sensitive human health outcomes under three adaptation scenarios.
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Health, Wellbeing and the Changing Structure of Communities Chapter 7
confidence, from very high (four dots) to low (one dot).The diagrams
for the proactive and incomplete adaptation scenarios are truncated at
the nearest whole °C within the range of temperature change in 2100
under three SSP scenarios used in panel (a) of SPM.3.
7.3.1.2 Projected Changes in Heat- and Cold-Related Exposure
and Related Health Outcomes
This section considers the broad impacts of projected changes in heat-
and cold-related exposure and related outcomes including mortality
and work productivity. Several of the most common heat- and cold-
related specific health outcomes (e.g., CVD) are assessed individually
in later sections of this chapter.
Population heat exposure will increase under climate change
(very high confidence). Since AR5 there has been considerable
progress with quantifying future human exposure to extreme heat
(Schwingshackl etal., 2021), especially as determined by different
combinations of SSPs and RCPs (Chambers, 2020; Cheng et al.,
2020; Jones etal., 2018; Liu etal., 2017; Ma and Yuan, 2021; Russo
etal., 2019). For example, Table7.1 shows projections of population
exposure to heatwaves, as expressed by the number of person-days,
for the 2061–2080 period aggregated by geographical region and
SSP/RCP. At the global level, projected future exposure increases
from approximately 15million person-days for the current period to
535billion person-days for high population growth under the high
GHG emission SSP3-RCP8.5 scenario, while for the low population
growth/high urbanisation and business as usual SSP5-RCP4.5
scenario, the exposure is substantially lower at 170billion person-
days. Spatial variations in future heatwave frequency and population
growth play out in the form of significant geographical contrasts in
exposure, with the largest increases projected for low latitude regions
such as India and significant portions of sub-Saharan Africa, where
increases in heatwave frequency and population are expected. Over
East Asia and especially eastern China, exposures are projected to
rise, with the effect of increases in heatwave frequency exceeding
the countering effect of projected reductions in population, especially
in non-urban areas. Further, for North America and Europe, where
rural depopulation is projected, the predominant driver of increases
in exposure is urban growth (Jones etal., 2018).
Comparisons of heatwave exposure for 1.5°C and 2.0°C warming
for different SSPs indicate strong geographical contrasts in potential
heatwave risk (high confidence). One global level assessment for a
1.5°C warming projects that low human development index countries
will experience exposure levels equal to or greater than the exposure
levels for very high human development index countries under a 2°C
warming (Russo, 2019). The same assessment also finds that holding
global warming below 1.5°C in tandem with achieving sustainable
socioeconomic development (e.g., SSP1 as opposed to SSP4) yields
reduced levels of heatwave exposure, especially for low human
development index countries, particularly across sub-Saharan Africa.
Similar findings were found in other global level assessments. Global
exposure to extreme heat increases almost 30times under a SSP3-
8.5 combination, with the average exposure for Africa 118 times
greater than historical levels, in stark contrast to the four-fold increase
projected for Europe. Compared to a SSP3-8.5 scenario, exposure was
reduced by 65% and 85% under the SSP2-4.5 and SSP1-2.6 scenarios,
respectively (Liu etal., 2017).
Regional level assessments of changes in population heat exposure for
Africa, Europe, the USA, China and India corroborate general findings
at the global level, that the impact of warming is amplified under
divergent regional development pathways (e.g., SSP4 – inequality)
compared to those fostering sustainable development (e.g., SSP1 –
sustainability) (high confidence) (Rohat et al., 2019a; Weber et al.,
2020; Broadbent etal., 2020; Dahl etal., 2019; Harrington and Otto,
2018; Rohat etal., 2019b; Vahmani etal., 2019; Huang and etal., 2018;
Zhang etal., 2020a; Liu etal., 2017). For some regions, such as Europe,
changes in exposure are projected to be largely a consequence of
climate change, while for others, such as Africa and to a lesser extent
Asia, Oceania, North America and South America, the interactive effects
of demographic and climate change are projected to be important
(Jones etal., 2018; Liu etal., 2017; Russo etal., 2016; Ma and Yuan,
2021) (medium confidence).
Compared to research that estimates the temperature only impacts of
climate change on heat-related mortality (see below), the number of
studies that explicitly model mortality responses considering various
combinations of SSPs and RCPs is small and mostly restricted to the
country or regional level. These studies point to increases in heat-
Table7.1 | Projected exposure to heatwaves in millions of person-days by region under different SSP/RCP combinations.
Region
Exposure in millions of person-days
Current SSP3-4.5 SSP5-4.5 SSP3-8.5 SSP5-8.5
Global
USA
North America
Europe
Latin America and
Caribbean
North Africa and Middle
East
Sub-Saharan Africa
Russia and Central Asia
South Asia
East Asia
Southeast Asia
Oceania
14,811
375
376
191
803
1,335
1,427
272
7,194
977
711
37
244,807
4,769
4,821
2,967
17,287
34,721
67,442
3,074
84,044
12,176
12, 452
247
168,488
8,671
8,778
3,775
10,856
23,160
41,339
1,951
53,655
10,855
9,146
492
534,848
10,802
10,990
7,326
45,612
65,072
158,290
6,554
146,709
35,381
60,909
822
374,269
19,646
20,153
9,969
28,435
43,648
96,054
4,360
94,288
31,918
47,141
1,158
7
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Chapter 7 Health, Wellbeing and the Changing Structure of Communities
related mortality especially amongst the elderly across a range of SSPs,
with the greatest increases under SSP5 and RCP8.5 (Rail etal., 2019;
Yang etal., 2021).
Estimates of heat-related mortality based solely on changes in
temperature point to elevated levels of global and regional level
mortality compared to the present, with the magnitude of this
increasing from RCP4.5 through to RCP8.5 (high confidence)
(Ahmadalipour and Moradkhani, 2018; Cheng etal., 2019; Kendrovski
etal., 2017; Lee etal., 2020; Limaye etal., 2018; Morefield etal., 2018).
Further support comes from the projection that heat-related health
impacts for a 2°C increase in global temperatures will be greater than
those for 1.5°C warming (very high confidence) (Dosio etal., 2018;
Mitchell etal., 2018; King and Karoly, 2017; Vicedo-Cabrera etal.,
2018a).
Estimates of future mortality that incorporate adaptation in addition to
temperature change point to increases in heat-related mortality under
global warming, albeit at lower levels than the case of no adaptation
(high confidence) (Anderson et al., 2018; Gosling et al., 2017; Guo
etal., 2018; Honda and Onozuka, 2020; Vicedo-Cabrera etal., 2018b;
Wang et al., 2018b). Whether adaptation is considered or not, the
consensus is Central and South America, southern Europe, southern
and Southeast Asia and Africa will be the most affected by climate
change in terms of heat-related mortality (high confidence). Similarly,
projections of the impacts of future heat on occupational health, worker
productivity and workability point to these regions as problematic
under climate change (high confidence) (Andrews etal., 2018; de Lima
etal., 2021; Dillender, 2021; Kjellstrom etal., 2018; Orlov etal., 2020;
Rao etal., 2020; Tigchelaar etal., 2020), especially for occupations
with high exposure to heat, such as agriculture and construction. This
accords with the findings from independent projections of population
heat exposure as outlined above (high confidence).
The effect of climate change on productivity is projected to reduce
GDP at a range of geographical scales (high confidence) (Borg etal.,
2021; Oppermann et al., 2021; Orlov et al., 2020). For example,
measuring economic costs using occupational health and safety
recommendations, it was estimated that RCP8.5 would result in a
2.4% reduction in global GDP compared to a 0.5% reduction under
RCP2.6 (Orlov etal., 2020). For the USA, it was estimated that the
total hours of labour supplied declined 0.11% (±0.004%) per degree
Celsius increase in global mean surface temperature for low-risk
workers and 0.53% (±0.01%) per degree Celsius increase for high-
risk workers exposed to outdoor temperatures (Hsiang etal., 2017).
Further, a systematic review of the literature indicates that extreme
heat exacts a substantial economic burden on health systems, which
bears implications for future heat-attributable healthcare costs
(Wondmagegn etal., 2019).
Since AR5, there has been an increase in the understanding of the extent
to which a warming world is likely to affect cold- or winter-related
health impacts. Future increases in heat-related deaths are expected
to outweigh those related to cold (high confidence) (Aboubakri etal.,
2020; Achebak etal., 2020; Burkart etal., 2021; Huber etal., 2020b;
Martinez etal., 2018; Rodrigues etal., 2020; Vardoulakis etal., 2014;
Weinberger etal., 2017; Weinberger etal., 2018a; Weitensfelder and
Moshammer, 2020). However, strong regional contrasts in heat- and
cold-related mortality trends are likely under a RCP8.5 scenario, with
countries in the Global North experiencing minimal to moderate
decreases in cold-related mortality while warm climate countries in the
Global South are projected to experience increases in heat-attributable
deaths by the end of the century (Gasparrini etal., 2017; Burkart etal.,
2021). Projections of the magnitude of change in the temperature-
related burden of disease do, however, demonstrate great variability,
due to the application of a wide range of climate change, adaptation
and demographic scenarios (Cheng etal., 2019).
A particular focus since AR5 has been the impact of climate change
on cities (see AR6 Chapter 6). Heat risks are expected to be greater
in urban areas due to changes in regional heat exacerbated by ‘heat
island’ effects (high confidence) (Doan and Kusaka, 2018; Heaviside
etal., 2016; Li etal., 2021; Rohat etal., 2019a; Rohat etal., 2019c;
Varquez et al., 2020; Wouters et al., 2017; Zhao et al., 2021), with
intra-urban scale variations in heat exposure attributable to land cover
contrasts and urban form and function (Avashia et al., 2021; Jang
et al., 2020; Macintyre et al., 2018; Schinasi etal., 2018). However,
further research is required to establish the health implications of
increasing chronic slow-onset extreme heat (Oppermann etal., 2021)
in addition to the acute health outcomes of UHI–heatwave synergies
under climate change. The latter is particularly important as studies
that address UHI–heatwave interactions have mainly focused on
changes in UHI intensity (e.g., Ramamurthy and Bou-Zeid (2017); Scott
etal. (2018)). Whether significant urban mortality anomalies arise from
the interplay of heatwaves and UHIs largely remains an open question
although at least one study demonstrated higher urban compared
to rural mortality rates during heatwaves (Ruuhela etal., 2021). The
benefits of the winter UHI effect for cold-related mortality remain
largely unexplored, but one study for Birmingham, UK, indicates the
winter UHI will continue to have a protective effect in future climate
(Macintyre etal., 2021).
7.3.1.3 Projected Impacts on Vector-Borne Diseases
The distribution and abundance of disease vectors, and the transmission
of the infections that they carry, are influenced both by changes in
climate and by trends such as human population growth and migration,
urbanisation, land use change, biodiversity loss and public health
measures. Each of these may increase or decrease risk, interact with
climate effects and may contribute to the emergence of infectious
disease, although there are few studies assessing future risk of
emergence (Gibb etal., 2020). Unless stated otherwise, the assessments
below are specifically for the effects of climate change on individual
diseases, assuming other determinants remain constant.
There is a high likelihood that climate change will contribute to increased
distributional range and vectorial capacity of malaria vectors in parts
of sub-Saharan Africa, Asia and South America (high confidence).
In Nigeria, the range and abundance of Anopheles mosquitoes are
projected to increase under both lower (RCP2.6) and especially under
higher emissions scenarios (RCP8.5) due to increasing and fluctuating
temperature, longer tropical rainfall seasons and rapid land use
changes (Akpan etal., 2018). Similarly, vegetation acclimation due to
elevated atmospheric CO
2
under climate change will likely increase the
7
1093
Health, Wellbeing and the Changing Structure of Communities Chapter 7
abundance of Anopheles vectors in Kenya (Le etal., 2019). Distribution
of Anopheles may decrease in parts of India and Southeast Asia, but
there is an expected increase in vectorial capacity in China (Khormi and
Kumar, 2016). In South America, climate change is projected to expand
the distributions of malaria vectors to 35–46% of the continent by 2070,
particularly species of the Albitarsis complex (Laporta etal., 2015).
Malaria infections have significant potential to increase in parts
of sub-Saharan Africa and Asia, with risk varying according to the
warming scenario (medium confidence). In Africa, where most
malaria is due to the more deadly Plasmodium falciparum parasite,
climate change is likely to increase the overall transmission risk due
to the likely expansion of vector distribution and increase in biting
rates (Bouma etal., 2016; M’Bra etal., 2018; Nkumama etal., 2017;
Ryan et al., 2015b; Tompkins and Caporaso, 2016a). The projected
effect of climate change varies markedly by region, with projections
for west Africa tending to indicate a shortening of transmission
seasons and neutral or small net reductions in overall risk, whereas
studies consistently project increases in southern and eastern Africa,
with potentially an additional 76million people at risk of endemic
exposure (10–12months yr
–1
) by the 2080s (Nkumama etal., 2017;
Ryan etal., 2015b; Semakula etal., 2017; Zaitchik, 2019; Leedale etal.,
2016; Murdock etal., 2016; Yamana etal., 2016; Ryan etal., 2020). In
sub-Saharan Africa, malaria case incidence associated with dams in
malaria-endemic regions will likely be exacerbated by climate change,
with significantly higher rates projected under RCP8.5 in comparison
Projected change in the abundance of Aedes aegypti
<-200 -100 0 >200
Potential abundance change (2090–2099) - (1987–2016)
100
(a) RCP2.6
(b) RCP8.5
Figure7.10 | Projected change in the potential abundance of Aedes aegypti over the 21st century (2090–2099 relative to 1987–2016) (Liu-Helmersson
etal., 2019).
7
1094
Chapter 7 Health, Wellbeing and the Changing Structure of Communities
to lower-emission scenarios (Kibret etal., 2016). Incidence of malaria
in Madagascar is projected to increase under RCP4.5 through RCP8.5
(Rakotoarison etal., 2018). Distribution of P. vivax and P. falciparum
malaria in China is likely to increase under RCPs higher than 2.6,
especially RCP8.5 (Hundessa etal., 2018). In India, projected scenarios
for the 2030s under RCP4.5 indicate changes in the spatial distribution
of malaria, with new foci and potential outbreaks in the Himalayan
region, southern and eastern states, and an overall increase in months
suitable for transmission overall, with some other areas experiencing a
reduction in transmission months (Sarkar etal., 2019).
Rising temperatures are likely to cause poleward shifts and overall
expansion in the distribution of mosquitoes Aedes aegypti and Aedes
albopictus, the principal vectors of dengue, yellow fever, chikungunya
and Zika (high confidence). Globally, the population exposed to
disease transmission by one of these vectors is expected to increase
significantly due to the combination of climate change and non-climatic
processes including urbanisation and socioeconomic inter-connectivity,
with exposure rates rising under higher warming scenarios (Kamal
etal., 2018; Kraemer etal., 2019). For example, approximately 50% of
the global population is projected to be exposed to these vectors by
2050 under RCP6.0 (Kraemer etal., 2019). The effect of climate change
alone is projected to increase the population exposed to Aedes aegypti
by 8–12% by 2061–2080 (Monaghan etal., 2018), and its abundance
is projected to increase by 20% under RCP2.6 and 30% under RCP8.5
by the end of the century (Liu-Helmersson etal., 2019; Figure7.10).
Exposure to transmission by Aedes albopictus specifically would be
highest at intermediate climate change scenarios and would decrease
in the warmest scenarios (Ryan etal., 2019). Under scenarios other
than RCP2.6, most of Europe would experience significant increases in
exposure to viruses transmitted by both vectors (Liu-Helmersson etal.,
2019).
Climate change is expected to increase dengue risk and facilitate
its global spread, with the risk being greatest under high emissions
scenarios (high confidence). Future exposure to risk will be influenced
by the combined effects of climate change and non-climatic factors
such as population density and economic development (Akter etal.,
2017). Overall, risk levels are expected to rise on all continents (Akter
et al., 2017; Messina et al., 2015; Rogers, 2015; Liu-Helmersson
etal., 2016; Messina etal., 2019). Compared to 2015, an additional
1 billion people are projected to be at risk of dengue exposure by
2080 under an SSP1-4.5 scenario, 2.25billion under SSP2-6.0, and
5billion under SSP3-8.5 (Messina etal., 2019). In North America, risk
is projected to expand in north-central Mexico, with annual dengue
incidence in Mexico increasing by up to 40% by 2080, and expand
from US southern states to mid-western regions (Proestos etal., 2015;
Colon-Gonzalez etal., 2013). In China, under RCP8.5, dengue exposure
would increase from 168million people in 142 counties to 490million
people in 456 counties by the late 2100s (Fan and Liu, 2019). In Nepal,
dengue fever is expected to expand throughout the 2050s and 2070s
under all RCPs (Acharya etal., 2018). In Tanzania, there is a projected
shift in distribution towards central and northeastern areas and risk
intensification in nearly all parts of the country by 2050 (Mweya etal.,
2016). Dengue vectorial capacity is projected to increase in Korea
under higher RCP scenarios (Lee etal., 2018a).
There are insufficient studies for assessment of projected effects of
climate change on other arboviral diseases, such as chikungunya
and Zika. Zika virus transmits under different temperature optimums
than does dengue, suggesting environmental suitability for Zika
transmission could expand with future warming (low confidence)
(Tesla etal., 2018).
Climate change can be expected to continue to contribute to the
geographical spread of the Lyme disease vector Ixodes scapularis
(high confidence) and the spread of tick-borne encephalitis and
Lyme disease vector Ixodes ricinus in Europe (medium confidence).
In Canada, vector surveillance of the black-legged tick I. scapularis
identified strong temperature effects on the limits of their occurrence,
on recent geographic spread, temporal coincidence in emergence of
tick populations and acceleration of the speed of spread (Clow etal.,
2017; Cheng etal., 2017). In Europe, increasing temperatures over the
1950–2018 period significantly accelerated the life cycle of Ixodes
ricinus and contributed to its spread (Estrada-Peña and Fernández-
Ruiz, 2020). Under RCP4.5 and RCP8.5 scenarios, projections indicate a
northward and eastward shift of the distribution of I. persulcatus and I.
ricinus, vectors of Lyme disease and tick-borne encephalitis in northern
Europe and Russia, with an overall large increase in distribution in
the second half of the current century (Popov and Yasyukevich, 2014;
Yasjukevich et al., 2018) and increases in intensity of tick-borne
encephalitis transmission in central Europe (Nah etal., 2020).
Climate change is projected to increase the incidence of Lyme
disease and tick-borne encephalitis in the Northern Hemisphere (high
confidence) (Figure 7.9). The basic reproduction number (R0) of I.
scapularis in at least some regions of Canada is projected to increase
under all RCP scenarios (McPherson etal., 2017). In the USA, a 2°C
warming could increase the number of Lyme disease cases by over
20% over the coming decades and lead to an earlier onset and longer
length of the annual Lyme disease season (Dumic and Severnini, 2018;
Monaghan etal., 2015).
Climate change is projected to change the distribution of schistosomiasis
in Africa and Asia (high confidence), with a possible increase in global
land area suitable for transmission (medium confidence). A global
increase in land area with temperatures suitable for transmission
by the three main species of Schistosoma (S. japonicum, S. mansoni
and S. haematobium) is projected under the RCP4.5 scenario for the
2021–2050 and 2071–2100 periods (Yang and Bergquist, 2018), but
regional outcomes are expected to vary. In Africa, shifting temperature
regimes associated with climate change are expected to lead to
reduced snail populations in areas with already high temperatures and
higher populations in areas with currently low winter temperatures
(Kalinda etal., 2017; McCreesh and Booth, 2014). Infection risk with
Schistosoma mansoni may increase by up to 20% over most of eastern
Africa over the next 20–50years but decrease by more than 50% in
parts of north and east Kenya, southern South Sudan and eastern
People’s Democratic Republic of Congo (PDRC) (McCreesh et al.,
2015), with a possible overall net contraction (Stensgaard etal., 2013).
In China, currently endemic areas in Sichuan Province may become
unsuitable for snail habitats, but currently non-endemic areas in
Sichuan and Hunan/Hubei provinces may see a new emergence (Yang
and Bergquist, 2018). In addition to the projected effects of temperature
7
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Health, Wellbeing and the Changing Structure of Communities Chapter 7
described above, distribution and transmission of schistosomiasis will
also be affected positively or negatively by changes in the availability
of freshwater bodies, which were not included in these models.
7.3.1.4 Projected Impacts on Waterborne Diseases
Climate change will contribute to additional deaths and mortality
due to diarrhoeal diseases in the absence of adaptation (medium
confidence) (see Figure 7.8). Risk factors for future excess deaths
due to diarrhoeal diseases are highly mediated by future levels of
socioeconomic development and adaptation. An additional 1°C
increase in mean average temperature is expected to result in a 7%
(95% CI, 3–10%) increase in all-cause diarrhoea (Carlton etal., 2016),
an 8% (95% CI, 5–11%) increase in the incidence of diarrheic E. coli
(Philipsborn etal., 2016) and a 3–11% increase in deaths attributable
to diarrhoea (WHO, 2014). WHO Quantitative Risk Assessments for the
effects of climate change on selected causes of death for the 2030s
and 2050s project that overall deaths from diarrhoea should fall due
to socioeconomic development but that the effect of climate change
under higher emission scenarios could cause an additional 48,000
deaths in children aged under 15years in 2030 and 33,000 deaths
for 2050, particularly in Africa and parts of Asia. In Ecuador, projected
increases in rainfall variability and heavy rainfall events may increase
diarrhoea burden in urban regions (Deshpande etal., 2020). A limit in
the assessable literature is a lack of studies in the highest risk areas
(Liang and Gong, 2017; UNEP, 2018).
Climate change is expected to increase future health risks associated
with a range of other WBDs and parasites, with effects varying by
region (medium confidence). WBDs attributable to protozoan parasites
including Cryptosporidium spp. and Giardia duodenalis (intestinalis)
are expected to increase in Africa due to increasing temperatures
and drought (Ahmed etal., 2018; Efstratiou etal., 2017). Recent data
suggest a poleward expansion of Vibrios to areas with no previous
incidence, particularly in mid- to high-latitude regions in areas where
rapid warming is taking place (Baker-Austin etal., 2017). The number
of Vibrio-induced diarrhoea cases yr
–1
increased in past decades in the
Baltic Sea region, and the projected risk of vibriosis will increase in
northern areas, where waters are expected to become warmer and
more saline due to reduced precipitation and have higher chlorophyll
concentrations (Escobar etal., 2015; Semenza etal., 2017).
The risk of Campylobacteriosis and other enteric pathogens could rise
in regions where heavy precipitation events or flooding are projected to
increase (medium confidence). In Europe, the risk of Campylobacteriosis
and diseases caused by other enteric pathogens could rise in regions
where precipitation or extreme flooding are projected to increase
(European Environment Agency, 2017), although incidence rates may
be further mediated by seasonal social activities (Rushton etal., 2019;
Williams et al., 2015b). Accelerated releases of dissolved organic
matter to inland and coastal waters through increases in precipitation
are expected to reduce the potential for solar ultraviolet inactivation of
pathogens and increase risks for associated WBDs (Williamson etal.,
2017). The combined relative risk for waterborne campylobacteriosis,
salmonellosis and diseases due to Verotoxin-producing Escherichia coli
was estimated to be 1.1 (i.e., a 10% increase) for every 1°C in mean
annual temperature, while by the 2080s, under RCP8.5, annual rates of
cryptosporidiosis and giardiasis could rise by approximately 16% due
to more severe precipitation events (Brubacher etal., 2020; Chhetri
etal., 2019).
7.3.1.5 Projected Impacts on Food-Borne Diseases
The prevalence of Salmonella infections is expected to rise as higher
temperatures enable more rapid replication (medium confidence).
Research from Canada finds a very strong association of salmonellosis
and other FBDs with higher temperatures, suggesting that climate
change could increase food safety risks ranging from increased public
health burden to emergent risks not currently seen in the food chain
(Smith and Fazil, 2019). In Europe, the average annual number of
temperature-related cases of salmonellosis under high emissions
scenarios could increase by up to 50% more than would be expected on
the basis of on population change alone by 2100 (Lake, 2017; European
Environment Agency, 2017). Warming trends in the southern USA may
lead to increased rates of Salmonella infections (Akil etal., 2014).
7.3.1.6 Projected Impacts on Pollution- and Aeroallergens-
Related Health Outcomes
Global air pollution-related mortality attributable directly to climate
change—the human health climate penalty associated with climate-
induced changes in air quality—is likely to increase and partially
counteract any decreases in air pollution-related mortality achieved
through ambitious emission reduction scenarios or stabilisation of
global temperature change at 2°C (medium confidence). Demographic
trends in aging and more vulnerable population are likely to be
important determinants of future air quality—a human health climate
penalty (high confidence).
Poor air quality contributes to a range of NCDs, including cardiovascular,
respiratory and neurological, commonly resulting in hospitalisation or
death. This section considers the possible risks for health of future
climate-related changes in ozone and PM. The climate penalty, the
degree to which global warming could affect future air quality, is better
understood for ozone than for PM (von Schneidemesser etal., 2020).
This is because increases in air temperature enhance ozone formation
via associated photochemical processes (Archibald etal., 2020; Fu and
Tian, 2019). The association between climate and PM is complex and
moderated by a diverse range of PM components as well as formation
and removal mechanisms (von Schneidemesser etal., 2020), added
to which is uncertainty about future climate-related PM sources such
as wildfires (Ford etal., 2018) and changes in aridity (Achakulwisut
etal., 2019). As noted in AR6 WGI Chapter 6 (Naik et al 2021), future
air quality will largely depend on precursor emissions, with climate
change projected to have mixed effects. Because of the uncertainty
in how natural processes will respond, there is low confidence in the
projections of surface ozone and PM under climate change (Naik
etal., 2021). This has implications on the levels of confidence in the
projections of the health climate penalty associated with climate-
induced changes in air quality (Orru etal., 2017; Orru etal., 2019; Silva
etal., 2017).
There is a rich literature on global and regional level projections of
air quality-related health effects arising from changes in emissions.
7
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Chapter 7 Health, Wellbeing and the Changing Structure of Communities
Comparatively few studies assess how changes in air pollution
directly attributable to climate change are likely to affect future
mortality levels. Projections indicate that emission reduction scenarios
consistent with stabilisation of global temperature change at 2°C or
below would yield substantial co-benefits for air quality-related health
outcomes (Chowdhury etal., 2018b; von Schneidemesser etal., 2020;
Silva etal., 2016c; Markandya etal., 2018; Orru etal., 2019; Shindell
etal., 2018) (high confidence). For example, by 2030, compared to
2000, it was estimated that globally and annually 289,000 PM2.5-
related premature deaths could have been avoided under RCP4.5
compared to 17,200 PM2.5-related excess premature deaths under
RCP8.5 (Silva etal., 2016c). Further, and notwithstanding estimated
reductions in global PM2.5 levels and an associated increase in the
number of avoidable deaths, the benefits of following a low emissions
pathway are expected to be apparent by 2100, with avoidable deaths
estimated at 2.39million deaths yr
–1
under RCP4.5. This contrasts with
the 1.31million deaths estimated under RCP8.5. A few projections
of the health-related climate penalty indicate a possible increase in
ozone and PM2.5-associated mortality under RCP8.5 (Doherty etal.,
2017; Orru etal., 2019; Silva etal., 2017).
At the global level for PM2.5, annual premature deaths due to
climate change were projected to be 55,600 (−34,300 to 164,000)
and 215,000 (−76,100 to 595,000) in 2030 and 2100, respectively,
countering by 16% the projected decline in PM2.5-related mortality
between 2000 and 2100 without climate change (Silva etal., 2017).
Similarly for ozone, the number of annual premature ozone-related
deaths due to climate change was projected to be 3,340 in 2030 and
43,600 in 2050, with climate change accounting for 1.2% (14%) of
the annual premature deaths in 2030 (2100) (Silva etal., 2017). These
global level projections average over considerable geographical
variations (Silva etal., 2017). Projections of the climate change effect
on ozone mortality in 2100 were greatest for East Asia (41 deaths
yr
–1
per million people), India (8 deaths yr
–1
per million people)
and North America (13 deaths yr
–1
per million people). For PM2.5,
mortality was projected to increase across all regions except Africa
(−25,200 deaths yr
–1
per million people) by 2100, with estimated
increases greatest for India (40 deaths yr
–1
per million people), the
Middle East (45 deaths yr
–1
per million people), East Asia (43 deaths
yr
–1
per million people) and the Former Soviet Union (57 deaths yr
–1
per million people). Overall, higher ozone-related health burdens
were projected to occur in highly populated regions, and greater
PM2.5 health burdens were projected in high PM emission regions
(Doherty etal., 2017).
For central and southern Europe, climate change alone could result
in an 11% increase in ozone-associated mortality by 2050. However,
projected declines in ozone precursor emissions could reduce the
EU-wide climate change effect on ozone-related mortality by up to
30%; the reduction was projected to be approximately 24% if aging
and an increasingly susceptible population were accounted for in
projections to 2050 (Orru etal., 2019). For the USA in 2069, the impact
of climate change alone on annual PM2.5- and ozone-related deaths
was estimated to be 13,000 and 3,000 deaths, respectively, with heat-
driven adaptation of air conditioning accounting for 645 and 315
of the PM2.5- and ozone-related annual excess deaths, respectively
(Abel etal., 2018). An aging population is a determinant of future air
quality-related mortality levels. An aging population along with an
increase in the number of vulnerable people may work to offset the
decrease in deaths associated with a low emission pathway (RCP4.5)
and possibly dominate the net increase in deaths under a business as
usual pathway (RCP8.5) (Chen etal., 2020; Doherty etal., 2017; Hong
etal., 2019; Schucht etal., 2015).
Complementing the longer-term changes in air quality arising from
climate change are those associated with air pollution sensitive short-
term meteorological events, such as heatwaves. Studies of individual
heat events (Garrido-Perez etal., 2019; Johansson etal., 2020; Kalisa
etal., 2018; Pu etal., 2017; Pyrgou etal., 2018; Schnell and Prather,
2017; Varotsos etal., 2019) and systematic reviews (Anenberg etal.,
2020) provide evidence for synergistic effects of heat and air pollution.
However, the health consequences of a possible additive effect of air
pollutants during heatwave events were heterogeneous, varying by
location and moderated by socioeconomic factors at the intra-urban
scale (Analitis etal., 2014; Fenech etal., 2019; Krug etal., 2020; Pascal
etal., 2021; Schwarz etal., 2021; Scortichini etal., 2018). This, combined
with the challenges associated with projecting future concentrations
of health-relevant pollutants during heatwave events (Jahn and Hertig,
2021; Meehl etal., 2018), makes it difficult to say with any certainty
that synergistic effects of heat and poor air quality will result in a
heatwave–air pollution health penalty under climate change.
The burden of disease associated with aeroallergens is anticipated to
grow due to climate change (high confidence). The incidence of pollen
allergy and associated allergic disease increases with pollen exposure,
and the timing of the pollen season and pollen concentrations are
expected to change under climate change (Beggs, 2021; Ziska etal.,
2019; Ziska, 2020). The overall length of the pollen season and total
seasonal pollen counts/concentrations for allergenic species such as
birch (Betula) and ragweed (Ambrosia) are expected to increase as a
result of CO
2
fertilisation and warming, leading to greater sensitisation
(Hamaoui-Laguel etal., 2015; Lake etal., 2017; Zhang etal., 2013).
Changes in pollen levels for several species of trees and grasses are
projected to increase annual emergency department visits in the USA
by between 8% for RCP4.5 and 14% for RCP8.5 by the year 2090
(Neumann et al., 2019) with the exposure to some pollen types
estimated to double beyond present levels in Europe by 2041–2060
(Lake etal., 2017). The prospect of increases in summer thunderstorm
events under climate change (Brooks, 2013) may hold implications
for changes in the occurrence of epidemic thunderstorm asthma
(Bannister et al., 2021; Emmerson et al., 2021; Price et al., 2021).
Similarly, projected alterations in hydroclimate under climate change
may bear implications for increased exposure to mould allergens in
some climates (D’Amato etal., 2020; Paudel etal., 2021).
7.3.1.7 Future Risks Related to Cardiovascular Diseases
Climate change is expected to increase heat-related CVD mortality
by the end of the 21st century, particularly under higher emission
scenarios (high confidence). Most modelling studies conducted since
AR5 project higher rates of heat-related CVD mortality throughout
the remainder of this century (Huang and etal., 2018; Li etal., 2015;
Li et al., 2018; Limaye et al., 2018; Zhang et al., 2018a; Silveira
et al., 2021a; Yang et al., 2021). CVD mortality in Beijing, China,
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Health, Wellbeing and the Changing Structure of Communities Chapter 7
could increase by an average of 18.4%, 47.8% and 69.0% in the
2020s, 2050s and 2080s, respectively, under RCP4.5 and by 16.6%,
73.8% and 134%, respectively, under RCP8.5 relative to a 1980s
baseline (Li etal., 2015). Projections of temperature-related mortality
from CVD for Beijing in the 2080s vary depending on RCP and
population assumptions (Zhang etal., 2018a). Projections for Ningo,
China, suggest heat-related years of life lost (YLL) could increase
significantly in the month of August by between 3 and 11.5times
over current baselines by the 2070s, even with adaptation (Huang
and et al., 2018). Yang and colleagues project that heat-related
excess CVD mortality in China could increase to approximately 6%
(from a 2010 baseline of under 2%) by the end of the century under
RCP8.5 and to over 3% under RCP4.5 (Yang etal., 2021). The future
burden of temperature-related myocardial infarctions in Germany is
projected to rise under high emissions scenarios (Chen etal., 2019),
while in the eastern USA, Limaye etal. (2018) projected an additional
11,562 annual deaths (95% CI: 2,641–20,095) by mid-century due to
cardiovascular stress in the population 65years of age and above.
CVD mortality in Brazil is projected to increase up to 8.6% by the end
of the century under RCP8.5, compared with an increase of 0.7% for
RCP4.5 (Silveira etal., 2021a).
It is important to note that the assessed studies typically take an
observed epidemiological relationship and apply future temperature
projections (often derived from regional climate projections) to
these relationships. Because the relationships between temperature
and CVD deaths are influenced by both climatic and non-climatic
factors (such as population fitness and aging), future projections are
highly sensitive to assumptions about interactions between climate,
population characteristics and adaptation pathways. Changes in air
quality because of climate change are an additional important factor.
For example, an assessment of future annual and seasonal excess
mortality from short-term exposure to higher levels of ambient
ozone in Chinese cities under RCP8.5 projected approximately 1,500
excess annual CVD deaths in 2050 (Chen etal., 2018). To the extent
possible, the relationships reported above reflect changes derived from
changes in heat exposure driven by climate change and not changes in
population demographics or air pollution exposure.
Climate change could impact CVD through other pathways, including
exposure to fine dust. For example, adult mortality attributable to fine
dust exposure in the American southwest could increase by 750 deaths
yr
–1
(a 130% increase over baseline) by the end of the century under
RCP8.5 (Achakulwisut etal., 2018).
7.3.1.8 Future Risks Related to Maternal, Foetal and Neonatal
Health
Additional research is needed on future impacts of climate change
on maternal, foetal and neonatal health. Maternal heat exposure is a
risk factor for several adverse maternal, foetal and neonatal outcomes
(Kuehn and McCormick, 2017), including foetal growth (Sun et al.,
2019) and congenital anomalies (Haghighi et al., 2021). There is
very limited research on this subject, an exception being Zhang etal.
(2020), which projected a 34% increase in congenital health disease
risk in the USA in 2025 and 2035 based on increased maternal extreme
heat exposure.
7.3.1.9 Future Health Risks Related to Food, Diets and Nutrition
7.3.1.9.1 Malnutrition
Climate change is projected to exacerbate malnutrition (high
confidence). Moderate and severe stunting in children less than five
years of age was projected for 2030 across 44 countries to be an
additional 570,000cases under a prosperity and low climate change
scenario (RCP2.6) to one million cases under a poverty and high climate
change scenario (RCP8.5), with the highest effects in rural areas
(Lloyd, 2018). Future DALYs lost due to protein-energy undernutrition
and micronutrient deficiencies without climate change have been
projected to increase between 2010 and 2050 by over 30million; with
climate change (RCP8.5), DALYs were projected to increase by nearly
10%, with the largest increases in Africa and Asia (Sulser etal., 2021).
The projected risks of hunger and childhood underweight vary under
the five SSPs, with population growth, improvement in the equality of
food distribution and income-related increases in food consumption
influencing future risks (Ishida etal., 2014; Hasegawa etal., 2015). A
review of 57studies projecting global food security to 2050 under the
SSPs concluded that global food demand was expected to increase by
35–56% between 2010 and 2050 (van Dijk etal., 2021). In the same
review, estimates of the change in population at risk of hunger by
2050 range between −91 to +8% if climate change is not considered
and between -91 to +30% if climate change is considered, with the
inclusion of climate change not leading to statistically significant
differences in projections (van Dijk etal., 2021).
7.3.1.9.2 Climate Change, Carbon Dioxide, Diets and Health
Climate change could further limit equitable access to affordable,
culturally acceptable, and healthy diets (high confidence). Climate
impacts on agricultural production and regional food availability will
affect the composition of diets, which can have major consequences for
health. Variable by region and context, healthy diets are an outcome
of the four inter-connected domains of sustainable food systems,
namely ecosystems, society, economics and health (Drewnowski etal.,
2020; Fanzo et al., 2020). Climate change limits the potential for
healthy diets through adverse impacts on natural and human systems
that are disproportionately experienced by low-income countries
and communities (FAO etal., 2021). Climate-driven droughts, floods,
storms, wildfires and extreme temperatures reduce food production
potential by diminishing soil health, water security and biological and
genetic diversity (Macdiarmid and Whybrow, 2019). Models project
that climate-related reductions in food availability, specifically fruit
and vegetables, could result in an additional 529,000 deaths a year by
2050 (Springmann etal., 2016b).
Diets reliant on marine fisheries and fish also face complex climate-
driven challenges (Hollowed et al., 2013). Rapidly warming oceans
(Cheng etal., 2020) limit the size of many fish and hamper their ability
to relocate or adapt; many commonly consumed fish, like sardines,
pilchards and herring, could face extinction due to these pressures
(Avaria-Llautureo et al., 2021). Other fisheries models project end-
of-century pollock and Pacific cod fisheries decreasing by >70% and
>35% under RCP8.5 (Holsman etal., 2020). Climate-driven increases
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Chapter 7 Health, Wellbeing and the Changing Structure of Communities
in marine mercury concentrations (Booth and Zeller, 2005) and harmful
algal blooms (Jardine etal., 2020) could impact dietary quality and
human health.
Global crop and economic models project higher cereal prices of up
to 29% by 2050 under RCP6.0, resulting in an additional 183million
people in low-income households at risk of hunger (Hasegawa etal.,
2018). Climate impacts on human health disrupt agricultural labour,
food supply chain workers and ultimately regional food availability
and affordability. A recent meta-analysis focused on sub-Saharan
Africa and Southeast Asia combined metrics of heat stress and labour
to project that a 3°C increase in global mean temperature, without
adaptation or mechanisation, could reduce agricultural labour capacity
by 30–50%, leading to 5% higher crop prices and a global welfare loss
of USD136billion (de Lima etal., 2021).
The nutritional density, including protein content, micronutrients and
B-vitamins, of wheat, rice, barley and other important food crops is
negatively affected by higher CO
2
concentrations (very high confidence)
(Mbow, 2019 ; Smith and Myers, 2018). Projections indicate negative
impacts on human nutrition by rising CO
2
concentrations by mid- to
late-century (Medek etal., 2017; Smith and Myers, 2018; Weyant etal.,
2018; Zhu etal., 2018; Beach etal., 2019). Staple crops are projected to
have protein and mineral concentrations decreased by 5–15% and B
vitamins up to 30% when the concentrations of CO
2
double above pre-
industrial levels (Ebi and Loladze, 2019; Beach etal., 2019; Smith and
Myers, 2018). Without changes in diets and accounting for nutrient
declines in staple crops, a projected additional 175 million people
could be zinc deficient and an additional 122 million people could
become protein deficient (Smith and Myers, 2018). Weyant etal. (2018)
projected that CO
2
-related reductions in crop zinc and iron levels
could result in 125.8million DALYs lost globally, with Southeast Asian
and sub-Saharan African countries most affected. Zhu et al. (2018)
estimated 600million people at risk from reductions in the protein,
micronutrient and B-vitamin content of widely grown rice cultivars in
Southeast Asia.
The combined effect of CO
2
and rising temperatures because of climate
change could result in a 2.4–4.3% penalty on expected gains by mid-
century in nutritional content because of technology change, market
responses and the fertilisation effects of CO
2
on yield (Beach etal.,
2019). These penalties are expected to slow progress in achieving
reductions in global nutrient deficiencies, disproportionately affecting
countries with high levels of such deficiencies.
7.3.1.10 Projected Impacts on Harmful Algal Blooms,
Mycotoxins, Aflatoxins and Chemical Contaminants
Harmful algal blooms are projected to increase globally, thus
increasing the risk of seafood contamination with marine toxins (high
confidence) (European Food Safety Authority etal., 2020; Gobler etal.,
2017; Barange etal., 2018; IPCC, 2019b; Wells etal., 2020). Climate
change impacts on oceans could generate increased risks of ciguatera
poisoning in some regions (medium confidence). Studies suggest
that rising sea surface temperatures could increase rates of ciguatera
poisoning in Spain (Botana, 2016) and other parts of Europe (European
Food Safety Authority etal., 2020).
Mycotoxins and aflatoxins may become more prevalent due to climate
change (medium agreement, low evidence). Models of aflatoxin
occurrence in maize under climate change scenarios of +2°C and
+5°C in Europe over the next 100 years project that aflatoxin B1
may become a major food safety issue in maize, especially in Eastern
Europe, the Balkan Peninsula and the Mediterranean regions (Battilani,
2016). The occurrence of toxin-producing fungal phytopathogens has
the potential to increase and expand from tropical and subtropical
regions into regions where such contamination does not currently
occur (Battilani, 2016).
Climate change may alter regional and local exposures to anthropogenic
chemical contaminants (medium agreement, low evidence). Changes
in future occurrences of wildfires could lead to a 14% increase in
global emissions of mercury by 2050, depending on the scenarios used
(Kumar etal., 2018a). Mercury exposure via consumption of fish may
be affected by warming waters. Warming trends in the Gulf of Maine
could increase the methyl mercury levels in resident tuna by 30%
between 2015 and 2030 (Schartup etal., 2019). An observed annual
3.5% increase in mercury levels was attributed to fish having higher
metabolism in warmer waters, leading them to consume more prey.
The combined impacts of climate change and the presence of arsenic in
paddy fields are projected to potentially double the toxic heavy metal
content of rice in some regions, potentially leading to a 39% reduction
in overall production by 2100 under some models (Muehe etal., 2019).
7.3.1.11 Future Risks Related to Mental Health and Well-Being
Climate change is expected to have adverse impacts on well-being,
some of which will become serious enough to threaten mental health
(very high confidence). However, changes (Hayes and Poland, 2018) in
extreme events due to climate change, including floods (Baryshnikova,
2019), droughts (Carleton, 2017) and hurricanes (Kessler etal., 2008;
Boscarino etal., 2013, Boscarino etal., 2017; Obradovich etal., 2018),
which are projected to increase due to climate change, directly worsen
mental health and well-being and increase anxiety (high confidence).
Projections suggest that sub-Saharan African children and adolescents,
particularly girls, are extremely vulnerable to negative direct and
indirect impacts on their mental health and well-being (Atkinson and
Bruce, 2015; Owen etal., 2016). The direct risks are greatest for people
with existing mental disorders, physical injuries, and compromised
respiratory, cardiovascular and reproductive systems, with indirect
impacts potentially arising from displacement, migration, famine and
malnutrition, degradation or destruction of health and social care
systems, conflict, and climate-related economic and social losses (high
to very high confidence) (Burke etal., 2018; Curtis etal., 2017; Hayes
etal., 2018; Serdeczny etal., 2017; Watts etal., 2019). Demographic
factors increasing vulnerability include age, gender and low
socioeconomic status, though the effect of these will vary depending
on the specific manifestation of climate change; overall, climate change
is predicted to increase inequality in mental health across the globe
(Cianconi et al., 2020). Based on evidence assessed in Section 7.2,
future direct impacts of increased heat risks and associated illnesses
can be expected to have negative implications for mental health and
well-being, with outcomes being highly mediated by adaptation, but
there are no assessable studies that quantify such risks. There may
be some benefits to mental health and well-being associated with
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Health, Wellbeing and the Changing Structure of Communities Chapter 7
fewer very cold days in the winter; however, research is inconsistent.
Any positive effect associated with reduced low-temperature days is
projected to be outweighed by the negative effects of increased high
temperatures (Cianconi etal., 2020).
Human behaviours and systems will be disrupted by climate change
in a myriad of ways, and the potential consequences for mental
health and well-being are correspondingly large in number and
complex in mechanism (high confidence). For example, climate
change may alter human physical activity and mobility patterns, in
turn producing alterations in the mental health statuses promoted by
regular physical activity (Obradovich and Fowler, 2017; Obradovich
and Rahwan, 2019). Climate change may affect labour capacity,
because heat can compromise the ability to engage in manual labour
as well as cognitive functioning, with impacts on the economic
status of individual households as well as societies (Kjellstrom
et al., 2016; Liu, 2020). Migrations and displacement caused by
climate change may worsen the well-being of those affected (Vins
et al., 2015; Missirian and Schlenker, 2017). Climate change is
expected to increase aggression through both direct and indirect
mechanisms, with one study predicting a 6% increase in homicides
globally for a 1°C temperature increase, although noting significant
variability across countries (Mares and Moffett, 2016). Broad
societal outcomes such as economic unrest, political conflict or
governmental dysfunction assessed in Section7.3.5 may undermine
the mental health of populations in the future (medium confidence).
Food insecurity presents its own severe risks for mental health and
cognitive function (Jones, 2017).
7.3.2 Migration and Displacement in a Changing Climate
Future changes in climate-related migration and displacement are
expected to vary by region and over time according to: (a) region-specific
changes in climatic drivers, (b) changes in the future adaptive capacity
of exposed populations, (c) population growth in areas most exposed
to climatic risks and (d) future changes in mediating factors such as
international development and migration policies (high agreement,
medium evidence) (Gemenne and Blocher, 2017; Cattaneo etal., 2019;
McLeman, 2019). This section assesses future risks associated with
changes in the frequency and/or severity of storms, floods, droughts,
extreme heat, wildfires and other events assessed in Section7.2 that
currently affect migration and displacement patterns, as well as the
impacts of emerging hazards, including average temperature increases
that may affect the habitability of settlements in arid regions and the
tropics, and sea level rise and associated hazards that threaten low-
lying coastal settlements. Studies assessed here consider projected
changes in future exposure to hazards over a variety of geographical
and temporal periods, with some considering changes in population
numbers in exposed areas. The uneven distribution of exposure of age
cohorts is typically overlooked in existing research. For example, people
younger than age 10 in the year 2020 are projected to experience a
nearly four-fold increase in extreme events under 1.5°C of global
warming and a five-fold increase under 3°C warming; such increases
in exposure would not be experienced by a person of the age of 55 in
2020 in their remaining lifetime under any warming scenario (Thiery
etal., 2021).
7.3.2.1 Region-Specific Changes in Climatic Risks
As outlined in 7.2, the most common drivers of observed climate-
related migration and displacement are extreme storms (particularly
tropical cyclones), floods and droughts (high confidence). The future
frequency and/or severity of such events due to anthropogenic climate
change are expected to vary by region according to future GHG
emission pathways (Naik et al 2021; Regional Chapters, this report),
with there being an increased potential for compound effects of
successive or multiple hazards (e.g., tropical storms accompanied by
extreme heat events (Matthews etal., 2019)). Table7.2 summarises
anticipated changes in future migration and displacement risks due to
sudden-onset climate events by region (and by sub-regions for Africa
and Asia, where climatic risks vary within the region).
In low-lying coastal areas of most regions, future increases in mean
sea levels will amplify the impacts of coastal hazards on settlements,
including erosion, inland penetration of storm surges and groundwater
contamination by salt water, and eventually lead to inundation of very
low-lying coastal settlements (high confidence) (Diaz, 2016; Hauer
etal., 2016; Neumann etal., 2015; Rahman etal., 2019; IPCC, 2019a).
Projections of the number of people at risk of future displacement by
sea level rise range from tens of millions to hundreds of millions by the
end of this century, depending on (a) the sea level rise scenario or RCP
selected, (b) projections of future population growth in exposed areas
and (c) the criteria used for identifying exposure. These latter measures
can include estimates of populations situated within selected elevations
above sea level (with 1 m, 2 m and 10 m being common parameters),
populations situated in 1-in-100 year floodplains or populations in
areas likely to be entirely inundated under specific RCPs (Neumann
etal., 2015; Hauer etal., 2016; Merkens etal., 2018; McMichael etal.,
2020; Hooijer and Vernimmen, 2021). As an illustrative example, an
estimated 267million people (error range = 197–347million at 68%
confidence level) worldwide lived within 2 m of sea level in 2020, 59%
of whom reside in tropical regions of Asia (Hooijer and Vernimmen,
2021). At a 1 m increase in sea level and holding coastal population
numbers constant, the number of people worldwide living within 2 m
of sea level expands to 410million (error range = 341–473million).
However, it is unlikely that coastal population growth rates will remain
constant at global or regional scales in future decades. At present,
coastal cities in many regions have relatively high rates of population
growth due to the combined effects of in-migration from other regions
and natural increase, with coastal areas of Africa having the highest
projected future population growth rates (Neumann et al., 2015;
Hooijer and Vernimmen, 2021; Box7.5). Further complicating future
estimates is that many large coastal cities are situated in deltas with
high rates of subsidence, meaning that locally experienced changes in
relative sea level may be much greater than sea level rise attributable
to climate change, thereby further increasing the number of people
exposed (Edmonds etal., 2020; Nicholls etal., 2021).
Sea level rise is not presently a significant driver of migration in
comparison with hazards assessed in Section7.2.6, but it has been
attributed as a factor necessitating the near-term resettlement of small
coastal settlements in Alaska, Louisiana, Fiji, Tuvalu and the Carteret
Islands of Papua New Guinea (Marino and Lazrus, 2015; Connell, 2016;
Hamilton etal., 2016; Nichols, 2019). In coastal Louisiana, communities
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Chapter 7 Health, Wellbeing and the Changing Structure of Communities
Table7.2 | Projected changes in sudden-onset climate events associated with migration and displacement by region.
Region
Main directions of current migration
flows (from Abel and Sander (2014))
Current climatic drivers of
migration and displacement
(Section7.2.6.1)
Expected changes in drivers (including confidence state-
ments) from IPCC WGI 2021 Technical Summary, 4.3.1–4.3.2
Asia
East and Southeast Asia: within countries and
between countries within same region.
South and central Asia: within countries and
between countries within same region; from
south Asia to Middle East, North America,
Europe.
West Asia: within countries and between
countries within the same region; to Europe
Floods, extreme storms, extreme heat
Increased risk of flooding in East, north, south and Southeast Asia due
to increases in annual mean precipitation (high confidence) and extreme
precipitation events in East, south, west central, north and Southeast Asia
(medium confidence); uncertainty regarding future trends in cyclones
(current trend = decreased frequency, increased intensity); higher average
temperatures across region (high confidence)
Africa
Within countries and between countries
within the same region; to Europe and the
Middle East
Floods, droughts, extreme heat
Decrease in total annual precipitation in northernmost and
southernmost parts of Africa (high confidence); west-to-east pattern of
decreasing-to-increasing annual precipitation in west Africa and east
Africa (medium confidence); increased risk of heavy precipitation events
that trigger flooding, across most parts of Africa (medium confidence);
increased aridity and drought risks in north Africa, southern Africa and
western parts of west Africa (medium-high confidence)
Europe
Within countries and between countries in
same region
Floods
Increased risk of floods across all areas of Europe except Mediterranean
areas (high confidence); higher risks of drought and fire weather in
Mediterranean areas (high confidence)
North America
Within countries and between countries in
same region
Floods, tropical cyclones (US Atlantic
and Caribbean coast), tornadoes,
wildfires
Increased frequency of heavy precipitation events across most areas
(high confidence); tropical cyclones to become more severe (medium
confidence); increased risk of drought and fire weather in central and
western North America
Central and
South America
Within countries and between countries in
same region; to North America, Europe
Floods (Central and South America),
extreme storms (Central America)
Increases in mean annual precipitation and extreme precipitation events
with higher risks of floods in most areas of South America (medium
confidence); increased risk of droughts in northeastern and southern
South America and northern Central America (medium confidence);
tropical cyclones becoming more extreme (medium confidence)
Australasia Displacement within countries Wildfires
Increases in fire weather across Australia and New Zealand (medium
confidence)
Small island
states
Within and between countries in same region
(e.g., Pacific Islands to Australia and New
Zealand; Caribbean islands to USA)
Extreme storms Potentially fewer but more extreme tropical cyclones (medium confidence)
tend to resist leaving exposed settlements until approximately 50% of
available land has been lost (Hauer etal., 2019). Movements away from
highly exposed areas may have longer-term demographic implications
for inland settlements (Hauer, 2017), but this requires further study.
Based on the available empirical evidence, sea level rise does not
appear to currently be a primary motivation for international migration
originating in small island states in the Indian and Pacific Oceans;
rather, economic considerations and family reunification appear to be
the dominant drivers (McCubbin etal., 2015; Stojanov and Du, 2016;
Heslin, 2019; Kelman etal., 2019). However, climatic drivers of migration
are anticipated to take on a much greater causal role in migration
decisions in coming decades (Thomas etal., 2020) and may discourage
return migration to small island states (van der Geest etal., 2020).
Even under best-case sustainable development scenarios, rising sea
levels and associated hazards create risks of involuntary displacement
in low-lying coastal areas and should be expected to generate a need
for organised relocation of populations where protective infrastructure
cannot be constructed (Horton and de Sherbinin, 2021; Hamilton etal.,
2016). In high emissions scenarios, low-lying island states may face
the long-term risk of becoming uninhabitable, creating the potential
for a new phenomenon of climate-induced statelessness (Piguet, 2019;
Desai etal., 2021).
Increased frequency of extreme heat events and long-term increases
in average temperatures pose future risks to the habitability of
settlements in tropical and subtropical regions, and may in the
long term affect migration patterns in exposed areas, especially
under high emissions scenarios (medium agreement, low evidence).
Greater research into the specific dynamics between extreme heat
and population movements is required in order to make an accurate
assessment of this risk. Recent studies suggest that future increases
in average temperatures could expose populations across wide areas
of the tropics and subtropics to ambient temperatures for extended
periods each year that are beyond the threshold for human habitability
(Pal and Eltahir, 2016; Im etal., 2017; Xu etal., 2020). This effect would
be amplified in urban settings where heat-island effects occur and
create a heightened need for air conditioning and other adaptation
measures. In addition to risks associated with average temperature
changes, Dosio etal. (2018) project that at 1.5°C warming, between
9% and 18% of the global population will be regularly exposed to
extreme heat events at least once in five years, with the exposure rate
nearly tripling with 2°C warming. How these changes in exposure to
high temperatures will affect future migration patterns, particularly
among vulnerable groups, will depend heavily on future adaptation
responses (Horton and de Sherbinin, 2021). Multiple country-level
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Health, Wellbeing and the Changing Structure of Communities Chapter 7
studies assessed in Section7.2 observe existing associations between
extreme heat, its impacts on agricultural livelihoods and changes in
rural-to-urban migration flows in parts of south Asia and sub-Saharan
Africa. A study conducted in Indonesia, Malaysia and the Philippines
suggests that an increased risk of heat stress would likely influence
migration intentions of significant numbers of people (Zander etal.,
2019).
7.3.2.2 Interactions with Non-climatic Determinants and
Projections of Future Migration Flows
Only a very small number of studies have attempted to make systematic
projections of future regional or global migration and displacement
numbers under climate change. Key methodological challenges for
making such projections include the availability of reliable data on
migration within and between countries, definitional ambiguity in
distinguishing climate-related migration from migration undertaken for
other reasons, and accounting for the future influence of non-climatic
factors. The most reliable example of such studies to date is a World
Bank report by Rigaud etal. (2018) that generated projections of future
internal population displacements in south Asia, sub-Saharan Africa
and Latin America by 2050 using multiple climate and development
scenarios, resulting in a very large range of possible outcomes (from
31 to 143million people being displaced, depending on assumptions).
An important outcome is the study’s emphasis on how the potential
for future migration and displacement will be strongly mediated by
socioeconomic development pathways in low- and middle-income
countries. Hoffmann etal. (2020) used meta-regression-based analyses
to project that future environmental influences on migration are likely
to be greatest in low- and middle-income countries in Latin America
and the Caribbean, sub-Saharan Africa, the Middle East and most of
continental Asia.
Research reviewed in AR4 and AR5 observed that at higher rates
of socioeconomic development, the in situ adaptive capacity of
households and institutions rises, and climatic influences on migration
correspondingly decline. Recent evidence adds further support for such
conclusions (high confidence) (Kumar etal., 2018b; Mallick, 2019; Gray
etal., 2020; Box7.5). Population growth rates are currently highest
in low-income countries (UN DESA Population Division, 2019), many
of which have high rates of exposure to climatic hazards associated
with population displacement, further emphasising the importance of
socioeconomic development and adaptive capacity-building. Although
country-specific scenarios for socioeconomic development and
population are embedded in SSPs, research into future migration flows
under climate change has not made great use of these. One of the few
studies to do so found that safe and orderly international migration
tends to increase wealth at regional and global scales in all SSP
narratives, which in turn reduces income inequality between countries
(Benveniste et al., 2021). International barriers to safe and orderly
migration may potentially impede progress towards attainment of the
objectives described in the SDGs and increase exposure to climatic
hazards in low- and middle-income countries (McLeman, 2019;
Benveniste etal., 2020).
Box7.5 | Uncertainties in projections of future demographic patterns at global, regional and
national scales
Projections of future numbers of people exposed to climate change-related hazards described in this chapter and elsewhere in this
report are heavily influenced by assumptions about population change over time at global, regional and national scales. One challenge
concerns global and regional variability of baseline data for current populations, which is typically aggregated from national censuses
that vary considerably in terms of frequency, timing and reliability, especially in low-income countries. A number of gridded mapping
dataset initiatives emerged in recent years to support population–environment modelling research at global and regional levels, common
ones being the Gridded Population of the World, the Global Rural Urban Mapping Project, and LandScan Global Population dataset
(McMichael etal., 2020). For future population projections at national levels, researchers commonly draw upon data generated by the
Population Division of the United Nations Department of Economic and Social Affairs, which publishes periodic projections for future
fertility, mortality, and international migration rates for over 200countries, the most recent projections being for the 2020 to 2100
period (UN DESA Population Division, 2019). There have been debates among demographers regarding the precision of DESA projections,
and whether these overestimate or underestimate future population growth in some regions (Ezeh etal., 2020). Population growth
rates are highly influenced by socioeconomic conditions, meaning that future population levels at local, national and regional scales
are likely to respond to relative rates of progress towards meeting the Sustainable Development Goals (Abel etal., 2016). The Shared
Socioeconomic Pathways (SSPs) used in climate impacts and adaptation research include a variety of assumptions about future mortality,
fertility and migration rates and provide a range of population growth scenarios that diverge after the year 2030 according to future
development trajectories (Samir and Lutz, 2017) and are then further modified and downscaled by researchers for national-level studies.
Understanding future risks of climate change will benefit from continued efforts by the international community to collect and share
data on observed population numbers and trends, and to work towards better projected data for population characteristics that strongly
influence vulnerability to climate risks, such as gender, age and indigeneity.
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Chapter 7 Health, Wellbeing and the Changing Structure of Communities
7.3.3 Climate Change and Future Risks of Conflict
Climate change may increase susceptibility to violent conflict, primarily
intra-state conflicts, by strengthening climate-sensitive drivers of
conflict (medium confidence). Section 7.2.7 described how climate
variability and extremes affect violent conflict through food and water
insecurity, loss of income and loss of livelihoods. Risks are amplified
by insecure land tenure, competing land uses and weather-sensitive
economic activities when they occur in the context of weak institutions
and poor governance, poverty and inequality (Section7.2.7). These
known, climate-sensitive risk factors allow projections of where
conflict is more likely to arise or worsen under climate change impacts
(see Chapters 1, 4, 5, 6 and 16) (Mach etal., 2020). However, there
is also the potential for new causal pathways to emerge as climate
changes beyond the variability observed in available datasets and
adaptation limits are met (Theisen, 2017; Mach et al., 2019; von
Uexkull and Buhaug, 2021).
Future violent conflict risk is highly mediated by socioeconomic
development trajectories (high confidence). Development trajectories
that prioritise economic growth, political rights and sustainability are
associated with lower conflict risk (medium confidence, low evidence).
Hegre etal. (2016) forecast future conflict under the SSPs and found
that SSP1, which prioritises sustainable development, is associated
with lower risks of conflict. Using data from sub-Saharan Africa,
Witmer et al. (2017) forecast conflict along the SSPs and find that
any increases in conflict that may be associated with climate change
could be offset by increases in political rights. Strong predictors of
future conflict are a recent history of conflict, large populations and
low levels of socioeconomic development (Hegre and Sambanis, 2006;
Blattman and Miguel, 2010).
Increases in conflict-related deaths with climate change have been
estimated but results are inconclusive (high agreement, medium
evidence). Some studies attempted to attribute observed conflict
outbreaks to changes in the physical environment and quantify future
conflict risk associated with climate change (von Uexkull and Buhaug,
2021; Theisen, 2017). Burke etal. (2015b) concluded that with each
one standard deviation increase in temperature, inter-personal conflict
increased by 2.4% and inter-group conflict by 11.3%. However, the
statistical methods have been criticised for under-representing the
known role that socioeconomic conditions and conflict history play
in determining the prevalence of violence (Buhaug etal., 2014; van
Weezel, 2019; Abel etal., 2019). Forecasting armed conflict is used
as a heuristic policy tool rather than a representation of the future
(Cederman and Weidmann, 2017) and forecasts have limitations. For
example, what constitutes and is experienced as hazards and as drivers
of conflict will shift over time as societies adapt to climate change
(Roche etal., 2020). The SSPs assume economic convergence between
countries and do not reflect growth disruptions (e.g., commodity price
shocks) that are often a key conflict risk factor (Dellink etal., 2017;
Buhaug and Vestby, 2019; Hegre etal., 2021).
Asia represents a key region where the peace, vulnerability and
development nexus has been analysed. In central, south and Southeast
Asia, there are large numbers of people exposed to changing climate
(Busby etal., 2018; Vinke etal., 2017; Reyer etal., 2017). South Asia
is one of the less peaceful regions in the world due to intra-state
communal conflict, international military conflict and political tension
(Wischnath and Buhaug, 2014; Huda, 2021), and many of the factors
that drive conflict risk (e.g. large populations with high levels of
inequality) are present (Nordqvist and Krampe, 2018). Despite these
risks, studies in this region also support the case for environmental
peacebuilding and resource sharing, as it relates to transboundary
water sharing (Berndtsson and Tussupova, 2020; Huda and Ali, 2018;
Section4.3.6; Section7.4.5.2).
There is little evidence of weather-related impacts on conflict risk or
prevalence, but the region is under-studied in general (Wischnath and
Buhaug, 2014; Nordqvist and Krampe, 2018). Climate stressors may
have contributed in part to local-level conflicts in Bangladesh and
Nepal (Sultana etal., 2019) and intensified water use conflict in peri-
urban areas (Roth etal., 2019). In the future there is the potential
for climate change to stretch the effectiveness of transboundary
water agreements by raising regional geopolitical tensions (Atef
etal., 2019; Scott etal., 2019) or to generate water use conflicts
between hydropower and irrigation within countries (Jalilov etal.,
2018). Climate change may have an impact on conflict by affecting
food security (Caruso et al., 2016; Raghavan et al., 2019). There
may be greater military involvement in humanitarian response to
cyclones, flooding and to other impacts of climate change that might
contribute to increased instability (Pai, 2008; Busby and Krishnan,
2017).
7.4 Adaptation to Key Risks and Climate
Resilient Development Pathways
With proactive, timely and effective adaptation, many observed and
projected risks for human health and well-being, health systems
and those associated with migration and conflict can be reduced
or potentially avoided (high confidence). Given the key health risks
identified in this chapter, adaptation that increases resilience and
sustainability will require moving beyond incremental adaptation to
sustained, adaptive management (Ebi, 2011; Hess etal., 2012) with
the goal of transformative change for integrated protection of human,
animal and ecosystem health. This includes differentiating adaptation
to climate variability from adaptation to climate change (Ebi and Hess,
2020). Health adaptation efforts are increasingly aiming to transition
to building climate-resilient and environmentally sustainable health
systems (WHO, 2015b; WHO, 2020a) and healthcare facilities,
emphasising service delivery including climate-informed health policies
and programmes; management of the environmental determinants of
health; emergency preparedness and management; health information
systems such as health and climate research, integrated risk monitoring
and early warning systems; and vulnerability, capacity and adaptation
assessments (Marinucci etal., 2014; Mousavi etal., 2020; WHO 2015a;
Centres for Disease Control , 2019; WHO, 2020a).
Migration can contribute to or work against adaptation goals and
progress, depending on the circumstances under which it occurs.
Policies that support safe and orderly movements of people, protect
migrant rights, and facilitate flows of financial and other resources
between sending and receiving communities are consistent with
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Health, Wellbeing and the Changing Structure of Communities Chapter 7
adaptive capacity-building and building sustainability and are part of
CRDPs (section 7.4.4).
Adaptation to prevent climate change from exacerbating conflict risk
involves meeting development objectives encapsulated in the SDGs.
Conflict-sensitive adaptation and climate-sensitive peacebuilding
offer promising avenues to addressing conflict risk, but their efficacy
is yet to be demonstrated through effective monitoring and evaluation
(Gilmore et al., 2018). Associations between environmental factors
and conflict are weak in comparison to socioeconomic and political
drivers. Therefore, meeting the SDGs, including Goal 16 on peace,
justice and strong institutions represent unambiguous pathways to
reducing conflict risk under climate change (Singh and Chudasama,
2021). Actively pursuing peace rather than taking conflict for granted
(Barnett, 2019), improving focus on gender within peacebuilding (Dunn
and Matthew, 2015; UNEP, 2021) and understanding how natural
resources and their governance interact with peacebuilding (Krampe
etal., 2021) present key elements of CRDPs for sustainable peace.
As documented across this chapter, there is a large adaptation deficit
for health and well-being, with climate change causing avoidable
injuries, illnesses, disabilities, diseases and deaths (high confidence).
Implementation of health adaptation has been incremental because
of significant constraints, primarily relating to financial and human
resources and because of limited research funding on adaptation
(Berrang-Ford et al., 2021). Current global investments in health
adaptation are insufficient to protect the health of populations and
communities (high confidence) from most climate-sensitive risks, with
large variability across and within countries and regions (UNEP, 2018).
Climate change adaptation in health is <1% of international climate
finance despite health being a priority sector in 54% of NDCs featuring
adaptation (UNEP, 2018).
As climate change progresses and the likelihood of dangerous risks
to human health continue to increase, there will be greater pressure
for more transformational changes to health systems to reduce future
vulnerabilities and limit further dangerous climate change (Ebi etal.,
2021a). Transformational resilience would need parallel investments
in social and health protections, including achieving the SDGs,
coupled with investments in mitigation (Ebi and Hess, 2020). Further,
investments in mitigating GHG emissions will not only reduce risks
associated with dangerous climate change but will improve population
health and well-being through several salutary pathways.
This chapter section identifies and assesses specific elements in
adapting to the risks identified in 7.2 and 7.3 and the opportunities for
fostering sustainability and pursuing CRDPs.
7.4.1 Adaptation Solution Space for Health and Well-
Being
The solution space is the space within which opportunities and
constraints determine why, how, when and who adapts to climate
change (Chapter 1). There is increased understanding of exposure
and vulnerabilities to climate variability and change, the capacities to
manage the health risks, the effectiveness of adaptation (including a
growing number of lessons learned and best practices), and the co-
benefits of mitigation policies and technologies (high confidence).
Effectively preparing for and managing the health risks of climate
change requires considering the multiple interacting sectors that
affect population health and the effective functioning of health
systems (high confidence). Given the wide range of causal pathways
through which climate change affects environmental and social
systems resulting in health impacts, a systems-based approach can
promote identifying, implementing and evaluating solutions that
support population health and health systems in the short and
longer term (high agreement, medium evidence). Such an approach
provides insights into policies and programmes that promote health
and well-being via multiple sectors (e.g., water and food safety and
security) and can ensure that health policies do not have adverse
consequences in other sectors (WHO, 2015b; Ebi and Otmani del
Barrio, 2017; Wright etal., 2021).
Figure 7.11 illustrates the context within which risks to health
outcomes and health systems emerge because of climate change.
The figure presents the emergence of risk from interactions between
specific types of climatic hazards, the exposure and vulnerability to
those hazards, and the responses taken within the health sector. The
figure also illustrates how health risks are situated within larger
interactions between the health system and other sectors and
systems, with underlying enabling conditions making adaptation
and transformation possible. Within this context, response options
can decrease the impacts of climate change on human health,
well-being and health systems by (a) reducing exposure to climate-
related hazards; (b) reducing vulnerability to such hazards and
(c) strengthening health system responses to future risks. Such
approaches are described as ‘Lateral Public Health’ and emphasise
the importance of involving community members and stakeholders in
the planning and coordination of activities (Semenza, 2021; Semenza,
2011). Lateral public health strives for community engagement (e.g.,
through access to technology in decision-making, such as low-cost
air sensors for wildfire smoke) in preparedness and response.
Effective health risk management incorporates the magnitude and
pattern of future climate risks as well as potential changes in factors
that determine vulnerability and exposure to climate hazards, such as
determinants of healthcare access, demographic shifts, urbanisation
patterns and changes in ecosystems (very high confidence). Climate
change is associated with shocks and stresses that can affect the capacity
and resilience of health systems and healthcare facilities (WHO, 2020a).
Figure7.12 illustrates some possible extents to which the capacity of
health systems could be reduced when exposed to a stress or shock,
and possible pathways forward, from collapse to transformation. The
subsequent sections of this chapter assess adaptation and mitigation
options to facilitate building the resilience of health systems and
healthcare facilities to recover better than before or to transform.
7
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Chapter 7 Health, Wellbeing and the Changing Structure of Communities
Health systems capacity and resilience to climate change-related shocks and stresses
Above average
Normal
Below average
Low
Shock
Stress
Transform
Recover better than before
Recover to pre-event state
Recover but worse than befor
e
Collapse
Time
Climate change adaptation
Prevention, preparednessResponseRecovery
Performance drop
Health system capacity Health system resilience
Vulnerability
Exposure
Hazard
Risk
Figure7.12 | Health systems capacity and resilience to climate change-related shocks and stresses. From WHO (2020).
Adaptation responses to climatic risks
Adaptation in other sectors
Vulnerability
Exposure
Hazard
Risk
Sustainable
livelihoods
Ch. 8
Biodiversity
Ch. 2; CCP 1
Ocean &
coastal systems
Ch. 3
Urban
systems
Ch. 6
Water & food
Ch. 4, 5
Adaptation responses
Can reduce vulnerability
Can reduce vulnerability
Can reduce exposure
Can reduce exposure
Health sector
adaptation
Figure7.11 | Context within which adaptation responses to climatic risks to health are implemented in the frame of interactions between health and
multiple other sectors.
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Health, Wellbeing and the Changing Structure of Communities Chapter 7
7.4.2 Adaptation Strategies, Policies and Interventions
7.4.2.1 Current State of Health Adaptation
Analysis of the NDCs to the Paris Agreement to determine how health
was incorporated, including impacts, adaptation and co-benefits,
concluded that most low- and middle-income countries referred to health
in their NDC (Dasandi etal., 2021). Figure7.13 shows the degree of
health engagement; this engagement is based on indicators measuring
the specificity and detail of health references within a country’s NDC.
Many vulnerable countries had high engagement of the health sector
in the country NDC. However, this analysis did not determine whether
the ambition expressed was sufficient to address the health adaptation
needs.
The 2018 WHO Health and Climate Change Survey, a voluntary
national survey sent to all 194 WHO member states, to which 101
responded, found that national planning on health and climate change
is advancing, but the comprehensiveness of strategies and plans need
to be strengthened. Implementing action on key health and climate
change priorities remains challenging and multi-sectoral collaboration
on health and climate change policy is evident, with uneven progress
(Watts etal., 2021). Approximately 50% of respondent countries had
developed national health and climate strategies, with over two-thirds
doing so within the preceding five years, and 48 of 101countries had
conducted a health vulnerability and adaptation assessment (Watts
etal., 2019). However, most countries reported only moderate or low
levels of implementation, with financing cited as the most common
barrier due to a lack of information on opportunities, in turn linked to a
lack of connection by health actors to climate change policy processes
and a lack of capacity to participate in national planning. A review of
public health systems in 34countries found that only slightly more
than half considered climate change impacts and adaptation needs
(Berry etal., 2018). Because the health risks of climate change often
vary within a country, sub-national assessments and plans are needed
to help local authorities protect and promote population health in a
changing climate (Aracena etal., 2021; Basel etal., 2020; Schramm
etal., 2020a).
7.4.2.2 Adaptation in Health Policies and Programmes
Health policies were historically not designed or implemented taking
into consideration the risks of climate change and as currently
structured are likely insufficient to manage the changing health
burdens in coming decades (very high confidence). The magnitude
and pattern of future health burdens attributable to climate change,
at least until mid-century, will be determined primarily by adaptation
and development choices. Current and future emissions will play an
increasing role in determining attributable burdens after mid-century.
Increased investment in strengthening general health systems, along
with targeted investments to enhance protection against specific
climate-sensitive exposures (e.g., hazard early warning and response
systems and integrated vector control programmes for VBDs)
will increase resilience if implemented to at least keep pace with
climate change (high confidence). Investments to address the social
determinants of health can reduce inequities and increase resilience
(high confidence) (Thornton etal., 2016; Marmot etal., 2020; Wallace
etal., 2015; Semenza and Paz, 2021).
Peer-reviewed publications of health adaptation to climate change in
low- and middle-income countries have typically focused on flooding,
rainfall, drought and extreme heat through improving community
resilience, DRR and policy, governance and finance (Berrang-Ford
etal., 2021; Scheelbeek etal., 2021). Health outcomes of successful
Health engagement score in
Nationally Determined Contributions (NDCs)
across countries
0 1 2 4
Health engagement score
3
5
Figure7.13 | Health engagement score in NDCs by country. Figure adapted from Dasandi etal. (2021).
7
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Chapter 7 Health, Wellbeing and the Changing Structure of Communities
adaptation have included reductions in infectious disease incidence,
improved access to water and sanitation and improved food security.
Figure7.14 shows a Sankey diagram of climate hazards, adaptation
responses and health outcomes. The figure highlights the range of
health adaptation responses that are discussed in more detail earlier
in this chapter and demonstrates the potential health benefit of
adaptation efforts that affect a broad range of health determinants.
Questions of the feasibility and effectiveness of health adaptation
options differ from those in other sectors because public health is a
societal enterprise that cuts across many different spheres of society.
Consequently, there are dependencies that lie outside the jurisdiction
of the health sector. All the health risks of a changing climate currently
cause adverse outcomes, with policies and programmes implemented
in at least some health programmes in some places. Policies and
programmes are continuously modified to increase effectiveness;
this will need to accelerate in a changing climate. Improvements are
needed as more is understood about disease aetiology, changing
socioeconomic and environmental conditions, obstacles to uptake and
other factors.
Policies and programmes for climate-sensitive health outcomes are
only beginning to incorporate the challenges and opportunities of
climate change, although this is critical for increasing resilience.
The fundamentals of many policies and programmes in a changing
climate will remain the same: implementing infectious disease control
programmes, preventing heat-related mortality and morbidity and
reducing the burden of other climate-related health endpoints, but
activities will need to explicitly account for climate change to continue
to protect health. Even with such attention to climate change, there
are limits to the feasibility and effectiveness of health adaptation
options for extreme heat, controlling emerging infectious diseases and
controlling cascading risk pathways.
As discussed in Sections 1.4.2 and 1.5, an adaptation option is
feasible when it is capable of being implemented by one or more
relevant actors. In the health sector, WHO, the United Nations
Children’s Fund (UNICEF) and other organisations provide technical
expertise to ministries of health, who then provide national to local
healthcare and public health services. Generally, the question is
less of overall feasibility, given the range of potential adaptation
options that have yet to be fully explored and implemented, but
more of readiness to buy into the adaptation efforts required
from health and other sectors. In specific contexts, feasibility also
depends on governance capacity, financial capacity, public opinion
and the distribution of political and economic power (Chapter 17).
In other words, adaptation to climate change is broadly feasible
with adequate investment and engagement, although this has yet
pH
Extreme precipitation and flooding
Drought
Heat
Precipitation variability
Sea-level rise
Ocean acidification
Other climate hazards
Behaviour change
Capacity building
(Micro)Financing
Green infrastructure
and climate-smart agriculture
Information and awareness
Physical infrastructure
Policy options
New technologies
Early warning systems
All cause mortality
Food security
WASH
Infectious disease
Mental health
Non-communicable disease
Health systems
Other health outcomes
Climate hazards Adaptation responses
Health (pathway)
outcomes
Figure7.14 | Sankey diagram of climate hazards, adaptation responses and health outcomes. CSA is climate-smart agriculture. Source: Scheelbeek etal. (2021).
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Health, Wellbeing and the Changing Structure of Communities Chapter 7
to materialise, and in specific contexts feasibility is contingent and
time-varying, and needs to be assessed at national to sub-national
scales. For example, a scoping review in the Pacific region noted the
following areas where further and significant investment and support
are needed to increase feasibility of climate and health action: (a)
health workforce capacity development, (b) enhanced surveillance
and monitoring systems and (c) research to address priorities and
their subsequent translation into practice and policy (Bowen etal.,
2021). Vulnerability, adaptation and capacity assessments include
consideration of the feasibility and effectiveness of priority health
adaptation options and can help decision makers identify strategies
for enhancing adaptation feasibility in specific contexts.
7.4.2.3 Adaptation Options for Vector-borne, Water-borne and
Food-Borne Diseases
Integrated vector control approaches are crucial to effectively manage
the geographic spread, distribution and transmission of VBDs associated
with climate change (high confidence). Some of the projected risks of
climate change on VBDs can be offset through enhanced commitment
to existing approaches to integrated case management and integrated
vector control management (Cissé etal., 2018; Confalonieri etal., 2017;
Semenza and Paz, 2021). Important components include enhanced
disease surveillance and early warning and response systems that can
identify potential outbreaks at sub-seasonal to decadal time scales
Table7.3 | Summary of adaptation options for key risks associated with climate-sensitive vector-, water- and food-borne diseases (VBDs, WBDs, FBDs).
Key
risk
Geographic
region(s) at
higher risk
Consequence that
would be consid-
ered severe and to
whom
Hazard conditions
that would con-
tribute to this risk
being severe
Exposure condi-
tions that would
contribute to this
risk being severe
Vulnerability con-
ditions that would
contribute to this
risk being severe
Adaptation
options with high
potential for
reducing risk
Selected key
references
VBDs Global
Increase in the
incidence of some
VBDs, such as malaria,
dengue and other
mosquito-borne
diseases, in endemic
areas and in new
risk areas (e.g.,
cities, mountains and
Northern Hemisphere)
Increased climatic
suitability for
transmission (e.g.,
enhanced vectorial
capacity through a
temperature shift)
Large increases in
human exposure to
vectors driven by
growth in human and
vector populations,
globalisation,
population mobility
and urbanisation
Few effective vaccines,
weak health systems,
ineffective personal
and household
protections,
susceptibility to
disease, poverty, poor
hygiene conditions,
insecticide resistance
and behavioural
factors
Improved housing,
better sanitation
conditions and
self-protection
awareness;
insecticide-treated
bed nets and indoor
spraying of insecticide;
broader access to
healthcare for the
most vulnerable;
establishment of
disease surveillance
and early warning
systems for VBDs;
cross-border joint
control of outbreaks;
effective vector
control; targeted
efforts to develop
vaccines
Cissé etal. (2018);
Semenza (2021);
Rocklöv and Dubrow.
(2020)
WBDs
Mostly
low- and
middle-income
countries
(Africa and
Asia); small
islands; global
for Vibrios
Increase in the
occurrence and
intensity of WBDs
such as Vibrios
(particularly V.
cholerae), diarrhoeal
diseases and other
waterborne GI
illnesses
Substantial changes
in temperature and
precipitation patterns,
increased frequency
and intensity of
extreme weather
events (e.g., droughts,
storms and floods),
ocean warming and
acidification
Large increases in
exposure, particularly
in flood-prone
areas with poor
sanitation and
favourable ecological
environments for WBD
pathogens
Poor hygiene
conditions, lack of
clean drinking water
and safe food, flood-
and drought-prone
areas and vulnerable
water and sanitation
systems
Improved WASH
conditions and
surveillance systems;
improved personal
drinking and eating
habits; behaviour
change
Brubacher etal.
(2020); Ford and
Hamner (2018); Lake
(2018); Levy etal.
(2018); Nichols etal.
(2018); Rocklöv etal.
(2021)
FBDs Global
Increase in the
occurrence and
intensity of FBDs
such as Salmonella
and Campylobacter,
including in
high-income countries
Substantial changes
in temperature and
precipitation patterns,
increased frequency
and intensity of
extreme weather
events (e.g., droughts,
storms and floods),
ocean warming and
acidification
Large increases in
exposure, particularly
in flood-prone
areas with poor
sanitation and
favourable ecological
environments for FBD
pathogens
Poor hygiene
conditions; lack
of clean drinking
water and safe
food; flood- and
drought-prone areas;
vulnerable water and
sanitation systems,
food storage systems,
food processes, food
preservation and cold
chain/storage
Improved WASH
conditions and
surveillance systems;
improved personal
drinking and eating
habits; behaviour
change; improved
food storage, food
processing, food
preservation and cold
chain/storage
Brubacher etal.
(2020); Ford and
Hamner (2018); Lake
(2018); Levy etal.
(2018); Nichols etal.
(2018); Rocklöv etal.
(2021)
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Chapter 7 Health, Wellbeing and the Changing Structure of Communities
(Rocklöv and Dubrow, 2020; Semenza and Zeller, 2014; Table7.3). In
many cases, the exposure dynamics of VBDs are strongly influenced by
socioeconomic dynamics that should be considered when developing
and deploying adaptation options (UNEP, 2018). This is especially
the case in low-income countries. For example, insufficient access
to sanitation and the presence of standing water are important
determinants of the presence of Aedes aegypti populations and
the pathogens that cause visceral leishmaniasis (L. donovani and L.
infantum) in urban and peri-urban areas. Low housing quality and lack
of refuse management are associated with higher rodent infestation.
Strategies expected to have important health co-benefits include those
that support health systems strengthening and ecosystem health,
improve access to health coverage, increase awareness and education
and address the underlying conditions of uneven development and a
lack of adequate housing and access to water and sanitation systems
in areas endemic to mosquito-borne diseases (Semenza and Paz, 2021;
Cross-Chapter BoxILLNESS in Chapter 2).
Adaptation options for climate-related risks for WBDs and FBDs
are strongly associated with wider, multi-sectoral initiatives to
improve sustainable development in low-income communities (high
confidence). Effective measures include improving access to potable
water and reducing exposure of water and sanitation systems to
flooding and extreme weather events (Brubacher etal., 2020; Cisse,
2019; Table7.3). This requires focusing on farm-level interventions that
limit the spread of pathogens into adjacent waterways, preventing
the ongoing contamination of water and sanitation systems and the
promotion of food-safe human behaviours (Levy etal., 2018; Nichols
et al., 2018). It is also important to implement well-targeted and
integrated WASH interventions, including at schools and ensuring
proper disposal of excreta and wastewater. Cities can integrate regional
climate projections into their engineering models to produce lower-
risk source waters and increase the resilience of water and sanitation
technologies and management systems under a range of climate
scenarios. Technologies can help abstract source waters from depth,
introduce or increase secondary booster disinfection, design or modify
systems to reduce residence times within pipes and/or coat exposed
pipes (Levy etal., 2018). Other efficient interventions include source
water protection, promoting water filtration, testing the presence of
waterborne pathogens in shellfish, imposing trade restrictions where
necessary and improving hygiene at all levels (Semenza and Paz,
2021). Needed actions include early warning and response systems,
strengthening the resilience of communities and health systems and
promoting ecosystem health, water safety plans and sanitation safety
plans (Brubacher etal., 2020; Cisse, 2019; Ford and Hamner, 2018;
Lake and Barker, 2018; Levy etal., 2018; Nichols etal., 2018; WHO
and International Water Association, 2009; WHO, 2016a; WHO, 2018b;
Semenza, 2021; Rocklöv etal., 2021).
7.4.2.4 Adaptation Options for Heat-Related Morbidity and
Mortality
Adaptations options for heat refer to strategies implemented at short
time scales such as air conditioning and HAPs, including heat warning
systems and longer-term solutions such as urban design and planning
and NbS (Table7.4).
To date, air conditioning is the main adaptation approach for
mitigating the health effects of high temperatures, especially in
relation to cardiorespiratory health (Madureira etal., 2021). However,
air conditioning may constitute a maladaptation because of its high
demands on energy and associated heat emissions, especially in high-
density cities (Eriksen et al., 2021; Magnan et al., 2016; Schipper,
2020), and also lead to ‘heat inequities’ as this is not an affordable or
practical option for many (Jay etal., 2021; Turek-Hankins etal., 2021).
HAPs link weather forecasts with alert and communication systems
and response activities, including public cooling centres, enhanced
heat-related disease surveillance and a range of individual actions
designed to reduce the health effects of extreme heat events such
as seeking shade and altering the pattern of work (McGregor etal.,
2015). While well-designed and operationalisable HAPs possess the
potential to reduce the likelihood of mortality from extreme heat
events (medium confidence) (Benmarhnia et al., 2016; Heo et al.,
2019b; Martinez-Solanas and Basagana, 2019; Martinez etal., 2019;
De’Donato etal., 2018), full process and outcome-based evaluations
of HAPs and their constituent components are lacking (Boeckmann
and Rohn, 2014; Chiabai etal., 2018b; Boeckmann and Rohn, 2014;
Nitschke etal., 2016; Diaz etal., 2019; Benmarhnia etal., 2016; Heo
etal., 2019a; Heo etal., 2019b; Ragettli and Roosli, 2019). Evaluations
of heatwave early warning systems as a component within HAPs
show inconsistent results in terms of their impact on predicting
mortality rates (Nitschke etal., 2016; Benmarhnia etal., 2016; Heo
etal., 2019a; Heo etal., 2019b; Ragettli and Roosli, 2019; Martinez
et al., 2019; De’Donato et al., 2018; Weinberger et al., 2018b),
indicating climate-based heat warning systems, which use a range of
heat stress metrics (Schwingshackl etal., 2021), are not sufficient as a
stand-alone approach to heat risk management (high confidence). To
support HAP and heat risk-related policy development, identification
and mapping of heat vulnerability ‘hot spots’ within urban areas have
been proposed (Chen etal., 2019; Hatvani-Kovacs etal., 2018)
A multi-sectoral approach, including the engagement of a range
of stakeholders will likely benefit the response to longer-term heat
risks through the implementation of measures such as climate-
sensitive urban design and planning that mitigates UHI effects (high
confidence) (Ebi, 2019; Jay etal., 2021; Alexander etal., 2016; Levy,
2016; Masson et al., 2018; McEvoy, 2019; Pisello etal., 2018). In
the shorter-term, potentially localised solutions can include awnings,
louvers, directional reflective materials, altering roof albedo, mist
sprays, evaporative materials, green roofs and building facades
and cooling centres (Jay et al., 2021; Macintyre and Heaviside,
2019; Spentzou et al., 2021; Takebayashi, 2018). NbS to reduce
heat that offer co-benefits for ecological systems include green and
blue infrastructure (e.g., urban greening/forestry and the creation
of water bodies) (Koc et al., 2018; Lai et al., 2019; Shooshtarian
etal., 2018; Ulpiani, 2019; Zuvela-Aloise et al., 2016; Hobbie and
Grimm, 2020). The implementation of climate-sensitive design and
planning can be constrained by governance issues (Jim etal., 2018)
and the benefits are not always evenly distributed among residents.
Implementation of climate-sensitive design and NbS does, however,
need to be carried out within the context of wider public health
planning because water bodies and moist vegetated surfaces provide
suitable habitats for a range of disease vectors (Nasir etal., 2017;
Tian et al., 2016; Trewin etal., 2020). Solutions recommended for
7
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Health, Wellbeing and the Changing Structure of Communities Chapter 7
managing exposure to heat in outdoor workers include improved
basic protection (including shade and planned rest breaks), heat-
appropriate personal protective equipment, work scheduling for
cooler times of the day, heat acclimation, improved aerobic fitness,
access to sufficient cold drinking water and on-site cooling facilities
and mechanisation of work (Morabito et al., 2021; Morris et al.,
2020; Varghese etal., 2020; Williams etal., 2020).
Most adaptation options were developed in high- and middle-income
countries and typically require significant financial resources for their
planning and implementation. Studies are needed of the benefits of
indigenous and non-Western approaches to managing and adapting
to extreme heat risk. Recently published reviews of approaches
to heat adaptation outline the nature and limitations of a range of
cooling strategies with optimal solutions for a number of settings
recommended (Jay etal., 2021; Turek-Hankins etal., 2021).
7.4.2.5 Adaptation Options for Air Pollution-related Health
Effects
As noted in Section 7.3.1.6, air pollution projections indicate
ambitious emission reduction scenarios or stabilisation of global
temperature change at 2°C or below would yield substantial co-
benefits for air quality-related health outcomes. Improvements in
air quality could be achieved by the deliberate adoption of a range
of adaptation options to complement mitigation measures such
as decarbonisation (e.g., renewable energy, fuel switching, energy
efficiency gains and carbon capture storage and utilisation) and
negative emissions technologies (e.g., bioenergy carbon capture and
storage, soil carbon sequestration, afforestation and reforestation
and wetland construction and restoration).
Adaptation options for air pollution include implementing ozone
precursor emission control programmes; developing mass transit/
efficient public transport systems in large cities; encouraging car-
pooling, cycling and walking (active transport); traffic congestion
charges; low emission zones in cities; integrated urban planning
implementing NbS such as green infrastructure for pollutant
interception and removal; managing wildfire risk regionally and
across jurisdictional boundaries; developing air quality warning
systems; altering activity on high pollution days; effective air
pollution risk communication and education; wearing protective
equipment such as face masks; avoiding solid fuels for cooking and
indoor heating; ventilating and isolating cooking areas; and using
portable air cleaners fitted with high-efficiency particulate air filters
(Abhijith etal., 2017; Carlsten etal., 2020; Cromar etal., 2020; Ding
Table7.4 | Summary of adaptation options for key health risks associated with heat.
Key risk
Geographic
region
Consequence
that would
be considered
severe, and to
whom
Hazard condi-
tions that would
contribute to
this risk being
severe
Exposure condi-
tions that would
contribute to
this risk being
severe
Vulnerability
conditions that
would contrib-
ute to this risk
being severe
Adaptation options
with high potential
for reducing risk
Selected key
references
Heat-related
mortality,
morbidity and
mental illness
Global but
especially where
temperature
extremes
beyond physical
and mental
health and
thermal comfort
threshold levels
are expected to
increase
Substantial
increase in
heat-related
mortality and
morbidity rates,
especially in
urban centres
(heat island
effect) and rural
areas (outside
workers),
outdoors in
general (sports
and related
activities) and
for people
suffering from
obesity, weak
cardiovascular
capacity /physical
fitness
Increased risk
of respiratory
disease and CVD
mortality
Loss of economic
productivity
Substantial
increase in
mental illness
compared to
base rate
Substantial
increase in
frequency and
duration of
extreme heat
events, especially
in cities where
heat will be
exacerbated by
UHI effects
Unintended
increases
in urban
temperatures
from
anthropogenic
heat (vehicles,
air conditioning,
urban
metabolism)
Increased number
of days with high
temperatures
in non-urban
settings such as
agricultural areas
Large increases
in urban heat and
population heat
exposure driven
by demographic
change (e.g.,
aging) and
increasing
urbanisation
Exposure will
increase amongst
agricultural and
construction
workers
Mortality/
morbidity:
Increases in
the number of
very young and
elderly and of
those with other
health conditions
such as lack of
physical fitness,
obesity, diabetes
and associated
comorbidities;
lack of
adaptation
capacity
Mental illness:
Lack of air
conditioning;
lack of access
to healthcare
systems and
services
Heat warning systems.
Improved building
and urban design
(including green and
blue infrastructure)
and passive
cooling systems,
acknowledging
that not all will
have access to air
conditioning
Broader
understanding of heat
hazard and better
access to public health
systems for the most
vulnerable
Application where
possible of renewable
energy sources
Communication
around drinking
water; availability
of clean water via
simple effective water
purification systems
in low water quality
settings; water spray
cooling
Mental health support
Benmarhnia etal.
(2016); Chen
etal. (2019); Jay
etal. (2021); Heo
etal. (2019b);
Martinez-Solanas
and Basagana
(2019); Morabito
etal. (2021);
Schwingshackl
etal. (2021)
7
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Chapter 7 Health, Wellbeing and the Changing Structure of Communities
Table7.5 | Summary of adaptation options for key health risks associated with air pollution.
Key risk
Geographic
region
Consequence
that would
be considered
severe and to
whom
Hazard conditions
that would con-
tribute to this risk
being severe
Exposure condi-
tions that would
contribute to
this risk being
severe
Vulnerability
conditions that
would contrib-
ute to this risk
being severe
Adaptation op-
tions with high
potential for
reducing risk
Selected key
references
Air
pollution-related
health effects
Global, but
especially in
regions with
existing poor
air quality,
particularly in
relation to PM
and ozone
Greatest climate
change driven
ozone-related
mortality is
expected for East
Asia and North
America
For PM the
highest
climate and air
quality-related
mortalities are
projected for
India, the Middle
East, Former
Soviet Union and
East Asia
Substantial
increase in air
pollution-related
mortality and
morbidity rates,
especially in
urban centres,
related to both
severe pollution
episodes and
longer-term
deterioration of
air quality
People
particularly
vulnerable
include those
with RTIs and
CVD
Increase in
mental illness
(depression) as
a result of poor
air quality and
visibility
Non-achievement
of emission
reduction targets
Substantial increase
in frequency
and duration of
meteorological
conditions
conducive to
the buildup of
both primary
and secondary
air pollutants
(e.g., greater
frequency of
calm atmospheric
‘blocking’
conditions) and
no long-term
improvement in air
quality at a range
of geographical
scales (global to
local)
Increase in
frequency and
intensity of
wildfires and dust
storms
Increase in the
intensity of UHIs,
especially in the
summer, and the
occurrence of ozone
episodes due to
anomalously high
urban temperatures
Large increases
in exposure to air
pollutants driven
by demographic
change (e.g.,
aging) and
increasing
urbanisation
For arid regions
increases in
exposure to dust
storms
Areas adjacent/
downwind of
major wildfires
For urban
populations
intensifying UHIs
and enhanced
formation of
secondary
pollutants
Increases in
the number of
very young and
elderly and those
with respiratory
or cardiovascular
conditions,
and lack of
adaptation
capacity (e.g.,
reduced reliance
on solid fuel for
cooking/heating)
Mental illness:
Lack of access
to healthcare
systems and
services
Air quality
management
policies, air
quality warning
systems, efficient
and cheap mass
transit systems,
integrated
urban planning
(including NbS
and green
infrastructure)
Broader
understanding
of air pollution
hazard and better
access to public
health systems
for the most
vulnerable
Application
where possible of
renewable energy
sources to reduce
emissions
Carlsten etal.
(2020); Doherty
etal. (2017);
Jennings etal.
(2021); Kumar etal.
(2019); Orru etal.
(2017); Orru etal.
(2019); Schumacher
and Shandas
(2019); Silva etal.
(2017); Voordeckers
etal. (2021)
etal., 2021; Holman etal., 2015; Jennings etal., 2021; Kelly etal.,
2021; Kumar et al., 2019; Masselot et al., 2019; Ng et al., 2021;
Riley, 2021; Voordeckers et al., 2021; Xu et al., 2017; Table 7.5).
While the range of air pollution adaptation options is potentially
extensive, barriers may need to be overcome to achieve successful
implementation, including financial, institutional, political (i.e. inter-
and intra-governmental) and social barriers (Barnes et al., 2014;
Ekstrom and Bedsworth, 2018; Fogg-Rogers etal., 2021; Schumacher
and Shandas, 2019).
7.4.2.6 Multi-sectoral Adaptation for Risks of Malnutrition
Adaptation to reduce the risk of malnutrition requires multi-sectoral,
integrated approaches (very high confidence). Adaptation actions
include access to healthy, affordable diverse diets from sustainable
food systems (high confidence); a combination of access to health—
including maternal, child and reproductive health— and nutrition
services, water and sanitation (high confidence); access to nutrition-
sensitive and shock-responsive social protection (high confidence);
and early warning systems (high agreement), risk sharing, transfer,
and risk reduction schemes such as index-based weather insurance
(medium confidence) (Mbow et al., 2019; Swinburn et al., 2019;
UNICEF/WHO/WBG, 2019; FAO et al., 2021; Macdiarmid and
Whybrow, 2019; Liverpool-Tasie etal., 2021). Common enablers across
adaptation actions that enhance the effectiveness and feasibility of
the adaptation include: education, women’s and girls’ empowerment
(high confidence), rights-based governance and peacebuilding social
cohesion initiatives such as the framework of the Humanitarian
Development and Peace Nexus (medium confidence).
Nutrition-sensitive and integrated agroecological farming systems
offer opportunities to increase dietary diversity at household levels
while building local resilience to climate-related food insecurity
(high confidence) (Bezner Kerr et al., 2021; IPES-Food, 2020; Altieri
et al., 2015) especially when gender equity, racial equity and
social justice are integrated (Bezner Kerr et al., 2021). Adaptation
responses include a combination of healthy, culturally appropriate
and sustainable food systems and diets; soil and water conservation;
7
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Health, Wellbeing and the Changing Structure of Communities Chapter 7
social protection schemes and safety nets; access to health services;
nutrition-sensitive risk reduction; community-based development;
women’s empowerment; nutrition-smart investments; increased policy
coherence; and institutional and cross-sectoral collaboration (high
agreement, medium evidence) (FAO etal., 2018; Mbow etal., 2019;
Pozza and Field, 2020; FAO etal., 2021; Table7.7). Nutrition security can
be enhanced through consideration of nutrient flows in food systems
(Harder et al., 2021).This ‘circular nutrient economy’ perspective
highlights the potential for adaptations throughout the food supply
chain, including sustainable production practices that promote
nutrient diversity and density, processing, storage, and distribution that
conserves nutrition; equitable access and consumption of available,
affordable, appropriate, and healthy foods; and waste management
that supports nutrient recovery (Harder etal., 2021; Boon and Anuga,
2020; FAO etal., 2021; Pozza and Field, 2020; Ritchie etal., 2018).
Traditional, indigenous and small-scale agroecology and regional food
systems provide context-specific adaptations that promote food and
nutrition security as well as principles of food sovereignty and food
systems resilience (HLPE, 2020; Bezner Kerr etal., 2021; IPES-Food,
2020; IPES-Food, 2018).
Table7.6 | Feasibility and effectiveness assessments of multi-sectoral adaptation for food security and nutrition.
Feasibility and effectiveness assessments
of multisectoral adaptation for food security and nutrition
Climate change impacts on food security and nutrition
Key risk: Malnutrition in all its forms linked to decline in food availability and increased
cost of healthy food
Adaptation option
Assessment results
Feasibility dimensions
Climate-resilient, nutrition-sensitive and agroecological food production
Sustainable and healthy diets (local, equitable, diverse)
Access to health, nutrition services and healthy environments (water and sanitation)
Early warning systems to prevent adverse effects on nutrition
Nutrition-sensitive social protection
Nutrition-sensitive risk reduction, risk sharing and insurance
Technological
Institutional
Geophysical
Social
Environmental
Agreement
Economic
Evidence
Effectiveness
Enabler relevance
Rights-based approach
and good governance
Humanitarian Development
and Peace nexus
Education
Women empowerment
= no data or not assessedna
na
HighMediumLow
Table7.7 | Summary of adaptation options for key risks associated with malnutrition.
Key risk
Geographic
region
Consequence that
would be consid-
ered severe and to
whom
Hazard condi-
tions that would
contribute to
this risk being
severe
Exposure condi-
tions that would
contribute to
this risk being
severe
Vulnerability
conditions that
would contrib-
ute to this risk
being severe
Adaptation options
with high potential
for reducing risk
Selected key
references
Malnutrition
due to
decline
in food
availability
and
increased
cost of
healthy food
Global, with
greater risks in
Africa, south
Asia, Southeast
Asia, Latin
America, the
Caribbean and
Oceania
Substantial number
of additional
people at risk of
hunger, stunting,
and diet-related
morbidity and
mortality, including
decreased mental
health and cognitive
function
Micro- and
macronutrient
deficiencies
Severe impacts
on low-income
populations from
LIMICs
Risks especially
high for groups
that suffer greater
inequality and
marginalisation
Climate changes
leading to
reductions in
crop, livestock
or fisheries
yields, including
temperature and
precipitation
changes and
extremes,
drought, and
ocean warming
and acidification
Large numbers of
people in areas
and markets
particularly
affected by
climate impacts
on food security
and nutrition
High levels
of inequality
(including gender
inequality) and
substantial
numbers of
people subject
to poverty or
violent conflict,
in marginalised
groups or with
low education
levels
Slow economic
development.
Ineffective
social protection
systems, nutrition
services, and
health services
Multi-sectoral
approach to
nutrition-sensitive
adaptation
and disaster
risk reduction/
management,
including food, health
and social protection
systems
Inclusive governance
involving
marginalised groups
Improved education
for girls and women
Maternal and child
health, water and
sanitation, gender
equality, climate
services and
social protection
mechanisms
Glover and Poole
(2019); Mbow
etal. (2019);
Swinburn etal.
(2019)
7
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Chapter 7 Health, Wellbeing and the Changing Structure of Communities
A feasibility and effectiveness assessment was conducted for six
adaptation strategies often used and recommended by the UN to
respond to malnutrition risks that combined a literature review and
expert judgment assessment of 80 peer-reviewed studies (UNSCN,
2010; Tirado et al. 2013; methods adapted from de Coninck et al.
(2018) and Singh etal. (2020)). Nineteen indicators of six dimensions
of feasibility (economic, technical, social, institutional, environmental
and geophysical) were considered. The lead time to initiate and the
expected longevity of each option were examined. Feasibility was
defined as how significant the reported barriers were to implement a
particular adaptation option. Highly feasible options were those where
no or very few barriers were reported. Moderately feasible were those
where barriers existed but did not have a strong negative effect on
the adaptation option (or evidence was mixed). Low feasibility options
had multiple barriers reported that could block implementation.
Effectiveness ratings were based on expert consultation and reflected
the potential of the adaptation option to reduce risk. The final
effectiveness and feasibility scores were categorised as high, medium
or low and reflect the combined results of all studies for a given
adaptation option (Table7.6).
Adaptive social protection programmes and mechanisms that can
support food insecure households and individuals include cash transfers
or public work programmes, land reforms, and extension of credit and
insurance services that reduce food insecurity and malnutrition during
times of environmental stress (Carter and Janzen, 2018; Johnson
et al., 2013; Alderman, 2016). For example, children from families
participating in Ethiopia’s Productive Safety Net Program experienced
improved nutritional outcomes, partly due to better household food
consumption patterns and reduced child labour (Porter and Goyal,
2016). School feeding programmes improve nutritional outcomes,
especially among girls, by promoting education, and by reducing child
pregnancy and fertility rates (Bukvic and Owen, 2017). Adaptive social
protection is most effective when it combines climate risk assessment
with DRR and wider socioeconomic development objectives (Davies
etal., 2013).
Transformative approaches towards healthier, more sustainable,
plant-based diets require integrated strategies, policies and
measures, including economic incentives for the agroecological
production and equitable access to and consumption of more
fruits, vegetables and pulses; inclusion of sustainability criteria in
dietary guidelines, labelling and public education programmes; and
promoting collaboration, good governance and policy coherence
(Glover, 2019).
7.4.2.7 Adaptation Options for Risks to Mental Health
Adaptation options for reducing mental health risks associated with
extreme weather include preventive and post-event responses (high
confidence) (Brown et al., 2017; Cohen, 2019; James et al., 2020;
Table7.8). Responses include improving funding and access to mental
healthcare, which is under-resourced (WHO, 2019a); surveillance
and monitoring of psychosocial impacts of extreme weather events;
community-level planning for mental health as part of climate-
resilience planning (Clayton et al., 2017); and mental health and
psychological first aid training for care providers and first responders
(Hayes etal., 2018; O’Donnell etal., 2021; Hayes etal., 2018; Taylor,
2020; Morgan etal., 2018; Sijbrandij etal., 2020). Legislation can
ensure access to services as well as establish a regulatory framework
(Ayano, 2018). Advanced disaster risk planning reduces post-event
mental health challenges. One example is from China, where pre-
Table7.8 | Summary of adaptation options for key risks associated with mental health.
Key Risk
Geographic
region
Consequence
that would
be considered
severe and to
whom
Hazard condi-
tions that would
contribute to
this risk being
severe
Exposure condi-
tions that would
contribute to
this risk being
severe
Vulnerability
conditions that
would contrib-
ute to this risk
being severe
Adaptation options
with high potential
for reducing risk
Selected key
references
Mental health
impacts in
response to
floods, storms,
and wildfires
Global; some
areas at greater
risk for storms,
flooding, or
wildfires
Substantial
increase in
mental illness
compared to
base rate
Increased
frequency of
major storms,
weather-related
flooding or
wildfires
Low-lying areas,
dry areas, urban
areas
Physical
infrastructure
that is vulnerable
to extreme
weather,
inadequate
emergency
response and
mental health
services, social
inequality
Improved urban
infrastructure,
warning systems, and
post-disaster social
support
Improved funding
and access to mental
healthcare
Improved surveillance
and monitoring of
mental health impacts
of extreme weather
events
Climate change
resilience planning
in the mental health
system (including at a
community level
Mental health first
aid training for care
providers and first
responders
Ali etal. (2020);
Ayano (2018);
Buckley etal.
(2019); Clayton
etal. (2017);
Hayes etal. (2019);
James etal. (2020);
Sijbrandij etal.
(2020)
7
1113
Health, Wellbeing and the Changing Structure of Communities Chapter 7
planning of temporary shelters resulted in significantly lower rates
of anxiety, depression and PTSD in the aftermath of flooding among
displaced people who accessed them (Zhong et al., 2020). Key
elements of successful initiatives include coordinated planning and
action between key regional agencies and governments with a focus
on improving accountability and removing barriers to implementation
and subsequent access to programmes (Ali et al., 2020). As an
example, following the 2019/2020 Australian bushfires, the federal
government allocated funds to support mental health through
free counselling for those affected, increased access to telehealth,
extended hours for mental health services and programmes designed
specifically for youth (Newnham etal., 2020).
Because mental health is fundamentally inter-twined with social and
economic well-being, adaptation for climate-related mental health
risks benefits from wider multi-sectoral initiatives to enhance well-
being, with the potential for co-benefits to emerge (high confidence).
Improvements in education, quality of housing, safety and social
protection support enhance general well-being and make individuals
more resilient to climate risks (Lund etal., 2018; Hayes etal., 2019).
Among Indigenous Peoples, connections to traditional culture and
to place are associated with health and well-being (Bourke et al.,
2018) as well as with resilience to environmental change (Ford etal.,
2020). As an example of the connection between infrastructure
improvements and mental health, a study of domestic rainwater
harvesting initiatives to promote household water security also
improved mental health in participating households (Mercer and
Hanrahan, 2017). Adaptive urban design that provides access to
healthy natural spaces—an option for reducing risks associated with
heat stress—also promotes social cohesion and mitigates mental
health challenges (high confidence) (Buckley et al., 2019; Clayton
etal., 2017; Jennings and Bamkole, 2019; Liu etal., 2020b; Mygind
etal., 2019; Marselle etal., 2020).
7.4.2.8 Adaptation Options to Facilitate Early-Warning and
Response Systems
Early warning systems are a potentially valuable tool in adapting to
climate-related risks associated with infectious diseases when based
on forecasts with high skill and when there are effective responses
within the time frame of the forecast (high confidence). Through
advanced seasonal weather forecasting that draws upon established
associations between weather/climate and infection/transmission
conditions, conditions conducive to disease outbreaks can be identified
months in advance, providing time to implement effective population
health responses (Morin et al., 2018). Most current early warning
systems are focused on malaria and dengue but there are examples
for other diseases, such as an early warning system developed
for Vibrios monitoring in the Baltic Sea (Semenza etal., 2017). An
early warning system for dengue outbreaks in Colombia based on
temperature, precipitation and humidity successfully detected 75%
of all outbreaks between one and five months in advance, detecting
12.5% in the same month (Lee et al., 2017b). Dengue warning
systems in Brazil, Malaysia and Mexico have generated satisfactory
results (Hussain-Alkhateeb etal., 2018). An effective early warning
system for malaria was implemented in the Amhara region of Ethiopia
(Merkord etal., 2017).
Early warning systems are effective at detecting and potentially
reducing food security and nutrition risks (high confidence). Examples
of proven systems include the United States Agency for International
Development (USAID) Famine Early Warning System, the Food and
Agricultural Organization’s Global Information and Early Warning
System and the World Food Programme’s Corporate Alert System. Such
systems are fundamental for anticipating when a crisis might occur
and setting priorities for interventions (Funk etal., 2019). Financial
investments to develop early warning systems are cost-effective and
reduce human suffering (Choularton and Krishnamurthy, 2019) (high
confidence). For instance, during the 2017 drought-induced food crisis
in Kenya, 500,000 fewer people required humanitarian assistance
than would have been expected based on past experiences; this was
largely due to timely and effective interventions triggered by the early
warning (Funk etal., 2018).
Early warning systems have been established for other climate-
sensitive health outcomes, such as respiratory diseases associated
with air pollution (Shih et al., 2019; Li and Zhu, 2018; Yang and
Wang, 2017). Early warning systems for non-heat extreme weather
and climate events, such as storms and floods, are designed to
protect human health and well-being; disaster risk management
organisations and institutions typically communicate these warnings
through their networks. Research is ongoing to extend the time
period for warnings.
7.4.2.9 Incorporating Disaster Risk Reduction into Health
Adaptation
Integrating health into national disaster risk management plans has
wider benefits for resilience and adaptation to climate change risks
(high confidence) (UNFCCC, 2017a; Watts etal., 2019). DRR, including
disaster preparedness, management and response, is widely recognised
as important for reducing health consequences of climate-related
hazards and extreme weather events (Keim, 2008; Phalkey and Louis,
2016). A systematic review by Islam etal. (2020) identified multiple,
ongoing challenges to integrating climate adaptation and DRR at
global and national levels, including a lack of capacity among key
actors and institutions, a lack of coordination and collaboration across
scales of government and general lack of funding—challenges that
are particularly relevant for the health sector. Global events, including
climate-related extreme events and public health emergencies of
international concern (for example, Ebola, Middle East respiratory
syndrome (MERS) and COVID-19) have influenced the development
of national public health preparedness and response systems and
attracted significant investment over the last two decades (Khan etal.,
2015; Murthy etal., 2017; Watson etal., 2017). The Sendai Framework
for Disaster Risk Reduction and the International Health Regulations
establish important global and regional goals for increasing health
system resilience and reducing health impacts from biological hazards
and extreme climate events (Aitsi-Selmi etal., 2015; Maini etal., 2017;
UNFCCC, 2017b; Wright etal., 2020). There are explicit links between
the health aspect of the Sendai Framework and UN SDGs 1, 2, 3, 4, 6, 9,
11, 13, 14, 15 and 17 (Wright etal., 2020). More specifically, reducing
the number of disaster-related deaths, illnesses and injuries, as well as
damage to health facilities are key indicators for achieving the goals
set out in the Sendai Framework (UNFCCC, 2017b).
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Chapter 7 Health, Wellbeing and the Changing Structure of Communities
The intersection of health and multi-sectoral DRR and manage-
ment, generally described as health emergency and disaster risk
management (health-EDRM), encompasses multi-sectoral approaches
from epidemic preparedness and response including the capacities
for implementing the International Health Regulations (IHR, 2005),
health systems strengthening and health systems resilience (Lo Iacono
et al., 2017; WHO 2019; Wright et al., 2020). Health-EDRM costs to
governments are notably lower than the cost of inaction (Peters etal.,
2019). Additional per capita costs in low-income countries have been
estimated to range from USD 4.33 (capital) and USD 4.16 (annual
recurrent costs), and in upper middle-income countries to an additional
USD 1.35 in capital costs and USD 1.41 in extra annual recurrent costs
(Peters et al., 2019). Adopting a health-EDRM approach supports the
systematic integration of health and multi-sectoral EDRM to ensure a
holistic approach to health risks and assists in the alignment of action in
health security, climate change and sustainable development (Chan and
Peijun, 2017; Dar etal., 2014; WHO, 2019; Wright etal., 2020).
Climate-informed health-EDRM is crucial for the climate resilience of
health systems (WHO, 2015a), particularly to account for additional
risks and uncertainties associated with climate change and allow for
well-planned, effective and appropriate EDRM and adaptation (Watts
etal., 2018a; WHO, 2013; WHO, 2015a). Potential coherent approaches
to addressing climate change and disaster risks to health include:
strengthening health systems; vulnerability and risk assessments that
incorporate disaster and climate change risk; building resilience of
health systems and health infrastructure; and climate-informed EWSs
(Banwell etal., 2018; Phalkey and Louis, 2016). However, a review of
DRR projects including climate change in south Asia found that the
health sector was the least represented with only 2% of 371 projects
relating to health (Mall etal., 2019), indicating a need to strengthen
the incorporation of climate change in health-EDRM. Current tracking
under the Sendai Framework of Disaster Risk Reduction 2015–2030
shows that most countries (particularly low-income countries and
lower middle-income countries) still lack robust systems for integrated
risk monitoring and early warning (UNEP, 2018). The incorporation of
DRR and management strategies into climate adaptation for health
and health systems at local scales is particularly important, given that
it is at local scales where health services are most often delivered
and where knowledge of specific needs and challenges is often
greatest (Amaratunga etal., 2018; Schramm etal., 2020a). Indigenous
knowledge has been shown to be valuable in DRR, with particularly
strong evidence existing for drought risk reduction in sub-Saharan
Africa (Fummi etal., 2017; Muyambo etal., 2017; Dube and Munsaka,
2018; Macnight Ngwese et al., 2018). In the USA, DRR strategies
that draw upon traditional knowledge and local expertise are being
incorporated into climate adaptation planning for health in a number
of indigenous communities under the ‘Climate-ready Tribes Initiative’
(Schramm etal., 2020b).
7.4.2.10 Monitoring, Evaluation and Learning
Monitoring, evaluation and learning (MEL) can assess the ability of
nations and communities to prepare for and adequately respond to the
health risks of climate change over time (high confidence) (Boyer etal.,
2020). MEL describes a process that includes baseline assessment,
prioritising actions and activities, identifying key indicators to track,
ongoing data collection and periodically considering new information
(Kruk et al., 2015). MEL determines whether adaptation options
achieved their goals and whether resources were used effectively and
efficiently (Boyer etal., 2020). One of the challenges for MEL in the
context of adaptation is that climate risks vary as a function of time,
location, socioeconomic development, demographics and activities in
other sectors (Ebi etal., 2018a). MEL indicators in the health sector
need to account for factors related to governance, implementation
and learning as well as for exposures, impacts and programmatic
activities, all of which are context dependent and are often outside
the health sector (Boyer etal., 2020; Ebi etal., 2018a; Fox etal., 2019).
No universal standardised approach exists for monitoring or evaluating
adaptation activities in the health sector (high confidence). Candidate
indicators of climate change health impacts and adaptation activity,
typically at the national level, are available (Bowen and Ebi, 2017;
Cheng and Berry, 2013; Kenney etal., 2016; Navi etal., 2017; WHO,
2015b). Indicators are best grouped by category of activity, that is,
vulnerability, risk and exposure; impacts; and adaptation and resilience
(Ebi etal., 2018a). As health adaptation expands, enhanced monitoring
will be needed to ensure that scientific advances are translated into
policy and practice. A promising initiative that emerged since the AR5
is the Lancet Countdown, which represents a global effort at tracking
various indicators of exposures, impacts, adaptation activities, finance
and media activity related to climate change and health (Watts etal.,
2018a), although this effort is principally focused on monitoring and
does not explicitly focus on evaluation adaptation efforts or learning
from adaptation efforts.
Community-based monitoring of adaptation responses to health
impacts, especially by Indigenous Peoples, has not been widely
undertaken, despite its potential to improve monitoring of and local
adaptation to environmental change (Kipp etal., 2019). The health
sector has been particularly weak at recognising the climate impacts
on and the adaptation needs of Indigenous Peoples and in engaging
Indigenous Peoples in monitoring progress (Ford etal., 2018; David-
Chavez and Gavin, 2018; Ramos-Castillo et al., 2017). Successful
adaptation to the health impacts of climate change in Indigenous
Peoples requires recognition of their rights to self-determination,
focusing on indigenous conceptualisations of well-being, prioritising
Indigenous knowledge and understanding the broader agenda of
decolonisation, health and human rights (high confidence) (Ford and
King, 2015; Green and Minchin, 2014; Hoy etal., 2014; Jones, 2019;
Jones etal., 2014; Mugambiwa, 2018; Nursey-Bray and Palmer, 2018).
Indicators should capture measures of processes that drive adaptation
readiness, including leadership, institutional learning and inter-
sectoral collaboration (Boyer et al., 2020; Ford and King, 2015) as
well as outcome measures such as the presence of programming
known to reduce risks (Ebi et al., 2018a). Additionally, indicators
related to scaling up of effective interventions and relying on the
implementation of science frameworks are important (Damschroder
etal., 2009; Theobald etal., 2018, 2020; Ebi etal., 2018a; Fox etal.,
2019). Measuring impacts attributable to climate change could be
addressed with a combination of indicators related to overall health
system performance and population vulnerability (Ebi etal., 2017; Ebi
etal., 2018a).
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Health, Wellbeing and the Changing Structure of Communities Chapter 7
7.4.3 Enabling Conditions and Constraints for Health
Adaptation
7.4.3.1 Governance, Collaboration and Coordination
Effective governance institutions, arrangements, funding and mandates
are key for adaptation to climate-related health risks (high confidence).
Without integration and collaboration across sectors, health adaptation
can become siloed, leading to less effective adaptation or even
maladaptation (Magnan etal., 2016; Fox etal., 2019). Integration and
collaboration include working laterally across national government
departments and agencies, as well as vertically from national
agencies to local governments and with the private sector, academia,
NGOs and civil society. In this context, top-down policy design and
implementation are complemented by bottom-up approaches that
engage community actors in programme design and draw upon their
local practices, perspectives, opinions and experiences. Opportunities
exist to better integrate public health into climate change discourse and
policymaking processes, and to strengthen public health partnerships
and collaborations (Awuor etal., 2020). Creating networks, integration
across organisations and jointly developed policies can facilitate cross-
sectoral collaboration (Bowen and Ebi, 2017).
7.4.3.2 Multi-sectoral Collaborations
Multi-sectoral collaborations aimed at strengthening the health sector
can generate multiple co-benefits in other sectors (high agreement,
medium evidence). Solutions for the health and well-being risks
described in 7.2 and 7.3 often have their origins in sectors that include
water, sanitation, agriculture, food systems, social protection systems,
energy and key components of urban systems such as housing and
employment (WHO, 2015a; Bowen et al., 2014b; Machalaba et al.,
2015; Confalonieri etal., 2015; Bowen etal., 2014a; Semenza, 2021).
Climate resilient development pursued in these other sectors, and
in cooperation with the health sector, simultaneously increases the
potential for adaptation and climate resilience in terms of health and
well-being (high confidence) (Ahmad etal., 2017; Watts etal., 2018b;
Levy and Patz, 2015; WHO, 2018a; Chiabai etal., 2018a; Dudley etal.,
2015; Zinsstag etal., 2018; Sherpa etal., 2014).
7.4.3.3 Financial Constraints
Financial constraints are the most referenced barrier to health
adaptation and so scaling up financial investments remains a key
international priority (very high confidence) (Wheeler and Watts, 2018;
UNFCCC, 2017a). AR5 estimated the costs of adaptation in developing
countries at between USD70billion and USD100billion annually in
the year 2050, but these are likely to be a significant underestimate,
particularly in the years 2030 and beyond (UNEP, 2014). National surveys
conducted by WHO identified financial constraints as a major barrier to
the implementation of health adaptation priorities (WHO, 2019b; Watts
etal., 2021). Novel research drawing on global financial transaction data
suggests that in 2019, global financial transactions with the potential
to deliver adaptation in the health and healthcare sector reached
USD 18.4 billion, driven by transactions in high- and upper middle-
income countries, with investment in Africa, Southeast Asia and the
eastern Mediterranean mostly stagnant (Watts etal., 2021).
There has been limited participation of the health sector in
international climate financing mechanisms (Martinez and Berry,
2018). Of 149 projects listed in the Adaptation Fund database in
October 2020, a large number were broad-based initiatives that
may have considerable indirect benefits for health systems, such as
enhanced disaster preparedness and food security, but none were
explicitly aimed at strengthening health systems or had directed funds
through ministries of health. A review of projects funded by the major
multi-lateral climate funds showed that less than 1.5% of dispersed
adaptation funding and less than 0.5% of overall funding have been
allocated to projects aimed at protecting health (WHO, 2015a). A
survey of national public health organisation representatives from
a mix of low-, middle- and high-income countries found that a lack
of political commitment, insufficient coordination across sectors and
inadequate funding for public health-specific adaptation initiatives
were common barriers to building climate resilience (Marcus and
Hanna, 2020). Under-investment in climate-specific initiatives in health
systems coincides with persistent under-investment in healthcare more
generally, especially in low- and middle-income countries (Schaferhoff
etal., 2019).
Adaptation financing does not often reach places where the
climate-sensitivity of the health sector is greatest (Weiler, 2019).
Financial constraints in Africa are one of the key reasons for slow
implementation of health adaptation measures (Nhamo and Muchuru,
2019). Strengthening health systems in vulnerable countries has the
potential to reduce current and future economic costs related to
environmental health risks, thus enabling reinvestment in the health
system and sustainable development (WHO, 2020a; WHO, 2015a).
Robust and comprehensive climate and health financing builds first
on core health sector investments (WHO, 2015a). Other potential
opportunities for resource mobilisation include health-specific funding
mechanisms, climate change funding streams and investments from
multi-sectoral actions and actions in health-determining sectors (WHO,
2015a). Incorporating climate change and health considerations into
disaster reduction and management strategies could improve funding
opportunities and increase potential funding streams (Aitsi-Selmi
et al., 2015). Reinforcing cross-sectoral governance mechanisms
maximises health co-benefits and economic savings by allowing for
multi-sectoral costs and benefits to be comprehensively considered
in decision-making (Belesova etal., 2016; WHO, 2020a; WHO, 2015b).
An additional financial need concerns health research, the existing
funding for which does not match what is needed to support the
implementation of the combined objectives of the UN 2030 Agenda
for Sustainable Development, the Sendai Framework for Disaster Risk
Reduction and the Paris Agreement (Green and Minchin, 2014; Ebi,
2016; Green etal., 2017).
7.4.3.4 Perceptions of Climate Change Risks and Links to
Adaptation
Adaptation decisions and responses to climate change can be
influenced by perceptions of risks, which are shaped by individuals’
characteristics, knowledge and experience (medium agreement,
medium evidence). Institutional and governmental responses are
critical for adapting to climate-related risks in health and other
sectors, but individual responses also are relevant, such as choosing
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Chapter 7 Health, Wellbeing and the Changing Structure of Communities
to implement adaptation measures. Individual responses are in turn
affected not only by capabilities but also by perceptions that climate
change is real and requires a response (Ogunbode et al., 2019).
Perceptions of climate risks are formed by experiences of changes in
local weather and extreme weather events (Sattler etal., 2018; Sattler
et al., 2020; van der Linden, 2015), observations of environmental
changes (Hornsey etal., 2016), experiences of and knowledge about
climate change impacts (Ngo etal., 2020; van der Linden, 2015) and
individual characteristics such as values and worldviews (Poortinga
et al., 2019) (high agreement, medium evidence). Risk perceptions
include both logical assessments about the likelihood and severity of
climate change impacts and affective feelings about those impacts.
On average, affective measures of risk perception are more strongly
associated with disaster preparation than cognitive measures
(Bamberg etal., 2017; van Valkengoed and Steg, 2019).
In addition to perceptions of risk, the likelihood that an individual will
implement behavioural adaptations or support relevant public policy is
affected by subjective assessments of the response options (Bamberg
et al., 2017; van Valkengoed and Steg, 2019; Akompab et al., 2013;
Carman and Zint, 2020; Hornsey etal., 2016; Brenkert-Smith etal., 2015).
Efficacy beliefs, social norms and subjective resilience also affect
adaptation behaviour (medium confidence), which has implications
for communication about the need for climate adaptation. Efficacy
beliefs represent the belief in one’s ability to carry out particular
action(s) and the belief that the action(s) will have the desired
outcome. Belief that one is personally able to complete a behaviour
is moderately associated with engaging in disaster preparations
(Navarro et al., 2021; van Valkengoed and Steg, 2019) and with
adaptation intentions (Burnham and Ma, 2017). Collective efficacy,
the belief that a group of people working together can achieve
a desired outcome, is important for participating in community
adaptation behaviours (Bandura, 1982; Chen, 2015; Thaker et al.,
2015). Related to this is response efficacy, a belief that a behaviour
will achieve its desired outcome, which is also moderately associated
with engaging in disaster preparations (van Valkengoed and
Steg, 2019). Collective efficacy can potentially be developed by
strengthening communication networks and social ties within a
community (Haas etal., 2021; Jugert etal., 2016). Norms describing
the adaptation strategies of others in a community, particularly
those with high social status, can either facilitate or inhibit individual
adaptation decisions (Neef etal., 2018; Smith etal., 2021).
Distinct from efficacy beliefs, subjective resilience is a more general
optimism or belief about one’s ability (Jones, 2019; Khanian et al.,
2019). Subjective resilience (Clare etal., 2017) can influence preferred
responses to climate change via assessment of one’s ability to engage
in specific response options. Identities can influence assessment of
subjective resilience. Place attachment, having a strong emotional
connection to a particular location, is weakly associated with disaster
preparation (Brügger etal., 2015). In some cases, place attachment
may inhibit adaptive responses, either by reducing perceptions of risk
or by making people reluctant to leave an area that is threatened
(De Dominicis et al., 2015; van Valkengoed and Steg, 2019). Place
attachment can also contribute to enhanced community resilience
(Khanian etal., 2019; Jones, 2019; Wang etal., 2021).
7.4.4 Migration and Adaptation in the Context of
Climate Change
7.4.4.1 Linkages between Migration, Adaptation and
Household Resilience
AR5 (Chapter 17) concluded that migration is often, though not in
all situations, a potential form of adaptation initiated by households.
Subsequent research indicates that the circumstances under which
migration occurs and the degree of agency under which household
migration decisions are made are important determinants of whether
migration outcomes are successful in terms of advancing the well-
being of the household and providing benefits to sending and
receiving communities (high confidence) (Adger etal., 2015; Cattaneo
etal., 2019; Cross-Chapter BoxMIGRATE in Chapter 7). Evidence from
refugee studies and general migration research indicates that higher
agency migration, in which migrants have mobility options, allows
migrants greater opportunities for integrating into labour markets at
the destination, makes it easier to remit money home and generally
creates conditions for potential benefits for migrant households and
for sending and receiving communities (International Organization for
Migration, 2019). Bilateral agreements that facilitate labour migration
have been identified as being especially urgently needed for Pacific
small island states (Weber, 2017).
Adaptive migration and the implied assumption that people can
or should simply move out of harm’s way is not a substitute for
investment in adaptive capacity-building (high agreement) (Bettini
and Gioli, 2016). Climate-related migration, and especially involuntary
displacement, often occurs only after in situ adaptation options have
been exhausted and/or where government actions are inadequate
(Adger etal., 2015; Ocello etal., 2015; Cross-Chapter BoxMIGRATE
in Chapter 7). The threshold at which household adaptation transitions
from in situ measures to migration is highly context specific and reflects
the degree of exposure to specific climate risks, mobility options
and the socioeconomic circumstances of the household and local
community (McLeman, 2017; Adams and Kay, 2019; Semenza and Ebi,
2019; Cross-Chapter BoxMIGRATE in Chapter 7). A consistent theme
in the research literature reviewed for all sections of this chapter is
that proactive investments in health, social and physical infrastructure,
including those not aimed specifically at climate risks, build societal
adaptive capacity and household resilience. In turn, expanding the
range of adaptation options available to households increases the
likelihood that, when migration does occur, it does so under conditions
of high agency that lead to greater chances of success. In communities
where climate-related migration and/or relocation is occurring or may
occur, policymaking and planning benefits from understanding the
cultural, social and economic needs of exposed populations and helps
in the identification of responses and policies that build resilience
(Hino etal. 2017)
7.4.4.2 Climate, Migration and Linkages to Labour Markets and
Social Networks
Adaptive climate-related migration is often closely related to
wage-seeking labour migration (medium confidence). Due to the
circumstances under which they move, climate-related migrants’
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Health, Wellbeing and the Changing Structure of Communities Chapter 7
destinations, labour market choices and returns from migration may be
more heavily constrained than those of other labour migrants (Jessoe
etal., 2018; Wrathall and Suckall, 2016).Within low- and middle-income
countries, rural–urban migrant networks are important channels for
remittances that may help build socioeconomic resilience to climate
hazards in sending areas (Porst and Sakdapolrak, 2020), with higher
levels of wage-seeking labour participation observed in climate-
sensitive locales in south Asia (Maharjan et al., 2020). Local-level
research in China and south Asia shows, however, that the potential
for remittances to generate improvements in household level adaptive
capacity is highly context specific, has significant gender dimensions
and depends on such factors as the nature of the hazard, the distance
migrated and the length of time over which remittances are received
(Banerjee etal., 2019a; Banerjee etal., 2019b). Social networks are a
key asset in helping climate migrants overcome financial and structural
impediments to their mobility, but these have their limits, particularly
with respect to international migration (Semenza and Ebi, 2019). Since
AR5, greater restrictions have emerged on movement between many
low- and high-income countries (not including those necessitated by
public health measures during the COVID-19 pandemic), a trend that,
if it continues, would generate additional constraints on destination
choices for future climate migrants (McLeman, 2019). Transnational
diasporic connections are a potential asset for building resilience
in migrant-sending communities highly exposed to climatic risks,
with migrants’ remittances potentially providing resources for long-
term resilience building, recovery from extreme events and reducing
income inequality (Bragg etal., 2018; Mosuela etal., 2015; Obokata
and Veronis, 2018; Shayegh, 2017; Semenza and Ebi, 2019). Safe
and orderly labour migration is consequently a potentially beneficial
component of wider cross-sectoral approaches to building adaptive
capacity and supporting sustainable development in regions highly
exposed to climate risks (McLeman, 2019).
7.4.4.3 Attitudes Towards Climate Migration
The success of climate-related migration as an adaptive response is
shaped by how migrants are perceived and how policy discussions
are framed (high agreement, medium evidence). The possibility that
climate change may enlarge international migrant flows has in some
policy discussions been interpreted as a potential threat to the security
of destination countries (Sow etal., 2016; Telford, 2018), but there is
little empirical evidence in peer-reviewed literature assessed for this
chapter of climate migrants posing significant threats to security at
state or international levels. There is also an inconsistency between
framing in some policy discussions of undocumented migration
(climate-related and other forms) as being ‘illegal’ and the objectives
of the Global Compact on Safe, Orderly and Regular Migration and
the Global Compact on Refugees (McLeman, 2019). Although climate-
related migrants are not officially recognised as refugees under the
1951 Convention relating to the Status of Refugees, terms such as
‘climate refugees’ are common in popular media and some policy
discussions (Høeg and Tulloch, 2018; Wiegel etal., 2019). The framing
of migration policy discussions is relevant, for example, in discussing
climate adaptation options for Pacific Island Countries, where there is
considerable disagreement over policies that range from a ‘migration
with dignity’ approach that would liberalise labour migration in the
Pacific region to those that see migration as a last resort option to
be avoided as much as possible (McNamara, 2015; Farbotko and
McMichael, 2019; Oakes, 2019; Remling, 2020). A more beneficial
policy framing in terms of ensuring that future migration contributes to
climate resilience and sustainable development has been established
since AR5 within the framework of the Global Compact for Safe,
Orderly and Regular Migration (see Section7.4.7.7).
Attitudes of residents in migrant-receiving areas with respect to
climate-related migration warrant consideration when formulating
adaptation policy (medium confidence). Existing research is modest
and difficult to generalise with respect to the impacts of climate-
related migration and displacement on social dynamics and stability in
receiving destinations, with outcomes being tied to the attitudes and
social acceptance of receiving communities and efforts to integrate
migrant arrivals into the community (Koubi and Nguyen, 2020).
Research from Kenya and Vietnam shows that residents of receiving
communities view environmental drivers as being legitimate reasons
for people to move and consequently tend not to stigmatise such
migrants (Spilker et al., 2020). In these examples, urban residents
viewed environmental motivations as being comparable to economic
reasons for migrating and did not see climate-related migrants as
posing any particular risks for receiving communities. However,
case studies from India suggest that a lack of recognition by local
authorities of climatic factors being legitimate drivers of rural–urban
migration may lead to discrimination against migrants in terms of
access to housing and other social protections, thereby undermining
household resilience (Chu and Michael, 2018).
7.4.4.4 Planned Relocation and Managed Retreats
There is high agreement among existing studies that immobile
populations often have high vulnerability and/or high long-term exposure
to climate hazards, and that non-climatic political, economic and social
factors within countries may strongly constrain mobility (Zickgraf,
2019; Ayeb-Karlsson etal., 2020; Cundill etal., 2021). Section7.2.6.2
highlighted the particular vulnerability of immobile populations in the
face of growing climatic risks. However, research suggests governments
should be slow to label such populations as being ‘trapped’ or to actively
promote relocations in the absence of local agreement that in situ
adaptation options have been exhausted (Adams, 2016; Farbotko and
McMichael, 2019). In the case of indigenous settlements, efforts made
to incorporate traditional knowledge in decision-making and planning
increase the potential for longer-term success (Manrique, 2018).
Considerable health implications can emerge within populations that
are relocated as part of a planned retreat, and represent an important
consideration for planners that requires greater research (Dannenberg
etal., 2019). Organised relocations are not inherently transformative
in their outcomes but, depending on the circumstances under which
they occur and on how issues of equity and respect for the rights of
those affected are implemented, relocation could potentially represent
a positive transformation (Siders etal., 2021).
Disruptive and expensive relocations of low-lying coastal settlements in
many regions would become increasingly necessary in coming decades
under high levels of warming (high confidence). Organised relocations
require long-term innovation, planning and cooperation on the part of
governments, institutions, affected populations and civil society (Hauer,
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Chapter 7 Health, Wellbeing and the Changing Structure of Communities
2017; Hino et al., 2017; Haasnoot et al., 2021; Moss et al., 2021).
Recent examples illustrate the substantial financial costs of organised
relocations, ranging from USD 10,000 per person in examples from Fiji
to USD 100,000 per person in coastal Louisiana, USA (Hino etal., 2017).
Organised relocations are politically and emotionally charged, may
not necessarily be seen as desirable by exposed populations and are
most successful when approached proactive and strategically to avoid
increasing the socioeconomic vulnerability of those who are relocated
(Jamero etal., 2017; Wilmsen and Webber, 2015; Chapin etal., 2016;
McNamara et al., 2018; Hauer et al., 2019; Bertana, 2020). Key
considerations for protecting the rights and well-being of people who
might need to be resettled include proactive communication with and
participation of the affected communities, availability of compensation,
livelihood protection and ensuring there is permanence and security of
tenure at the relocation destination (Tadgell etal., 2018). Availability
of funds for resettlement, how to manage relocation from communally
owned lands, how to value privately owned land to be abandoned and
the potential for loss and damage claims are just some of the many
potential complications (Marino, 2018; McNamara et al., 2018). As
a proactive option, researchers in Bangladesh have suggested the
creation of ‘migrant-friendly towns’ to provide options for autonomous
relocation from hazardous areas (Khan and Huq, 2021).
7.4.5 Adaptation Solutions for Reducing Conflict Risks
There has been increased activity within the international community
to understand and address climate–conflict linkages since AR5, with
high level actions including the UN Climate Security Mechanism,
launched in 2018 and tasked with providing integrated climate
risk assessments to the United Nations Security Council and other
UN bodies in partnership with UN and external actors (DPPA etal.,
2020). G7 governments initiated an integrated agenda for resilience
(Rüttinger etal., 2015) and the Berlin Call for Action in 2019 sought a
foreign policy platform to address climate security concerns, focusing
on risk-informed planning, enhanced capacity for action within the UN
and improvements to operational response to climate security risks
(Federal Foreign Office, 2019). The non-peer-reviewed literature that
currently addresses these policy dimensions is often generated by a
small number of consultancies funded by governments from the Global
North and can lack diverse perspectives and priorities.
7.4.5.1 Environmental Cooperation and Peacebuilding
The environment can form the basis for active peacebuilding, and
a sustainable natural environment is important for ongoing peace
(high agreement, medium evidence). EP is a framework increasingly
utilised to understand the diverse ways in which the natural
environment supports peace and can be utilised in peacebuilding;
key tenets include preserving the natural environment such that
degradation does not contribute to violence, protecting natural
resources during conflict and using natural resources to support
post-conflict economic recovery (Kron, 2019). EP frames natural
resources as facilitating peace rather than driving conflict (Dresse
et al., 2019) with emerging literature analysing what this means
in practice (Kovach and Conca, 2016; Krampe, 2017; Ide, 2019;
Ide etal., 2021; Johnson, 2021; Kalilou, 2021). There is emergent
evidence for the success of EP pathways. For example, a natural
resource sharing agreement on the Kenya–Uganda border was able
to reconcile spatial, logistical and conceptual barriers to addressing
climate risks in development contexts (Abrahams, 2020). However,
the long-term impacts of EP approaches on sustaining peace are
yet to be monitored and evaluated (Ide and Tubi, 2020). EP may be
successful depending on the context and the element of peace being
built (Johnson, 2021) or undermine processes when environmental
arguments are co-opted for geopolitical purposes (Barquet, 2015) or
to depoliticise conflict (Ide, 2020).
Formal institutional arrangements for natural resource management
can contribute to transnational cooperation (high confidence) (see also
Chapter 4). Evidence from transboundary water sharing agreements
provides evidence for cooperation rather than conflict over resources
(Timmerman et al., 2017; Timmerman, 2020; Dinar et al., 2015).
Transboundary water agreements and river basin organisations help
build robust institutions that facilitate trust and relationship building
that have benefits in other domains (strong agreement, medium
evidence) (Dombrowsky, 2010; Krampe and Gignoux, 2018; Barquet
etal., 2014; Ide and Detges 2018). However, outcomes can be mixed,
and the international and top down nature of these approaches may
limit their transferability to intra-state conflicts at local levels (Rigi and
Warner, 2020; Ide etal., 2021; Krampe etal., 2021).
7.4.5.2 Adaptation in Fragile Settings
Climate-resilient peacebuilding has the potential to limit the impact
of future climate change on peace efforts (medium confidence).
Practical guidance has been developed, driven by policy concerns on
climate–conflict links. The United Nations Environment Programme
(UNEP), the European Union and Adelphi have developed a toolkit
for addressing climate fragility risks in peacebuilding, adaptation
and livelihoods support (UNEP etal., 2019). Crawford etal. (2015)
provide recommendations for climate-resilient peacebuilding
consistent with the UN Secretary General’s five peacebuilding
principles, including integrating ex-combatants through the
construction of climate-resilient infrastructure, using climate impacts
as a platform to engage previously conflicting groups, developing
national DRR and management strategies, and climate-proofing
economic development activities. The USAID, in a report prepared
for the Adaptation Thought Leadership and Assessments (ATLAS)
programme (Adelphi & Chemonics International, 2020) that drew
upon resilience and peacebuilding programmes in the Horn of Africa,
recommend two critical conditions to ensure activities address
compound climate fragility risks. Firstly, conducting local analyses
of the links between climate, conflict and fragility to identify specific
risks to target and, secondly, ensuring long-term commitment with a
focus on participation and flexibility.
Conflict-sensitive adaptation that focuses on institutional frameworks,
conflict management and governance mechanisms has the potential
to address complex interacting risks and emergencies over the long
term (medium agreement, limited evidence) (Scheffran et al., 2012;
Matthew, 2018; Okpara et al., 2018). However, most adaptation
activities are planned and implemented under development or climate
finance funds without systematic integration of conflict sensitivity,
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Health, Wellbeing and the Changing Structure of Communities Chapter 7
and National Adaptation strategies rarely and only implicitly address
conflict and potential changes to power relations (Tänzler etal., 2019).
Practitioners and policy researchers have attempted to address this
gap by developing guidance and delivering training (e.g., Tänzler etal.
(2019); Bob and Bronkhorst (2014)). However, there are real challenges
relating to discounting indirect impacts on conflict and maladaptation
(Asplund and Hjerpe, 2020) and risks of unintended outcomes
(Mirumachi et al., 2020). Crawford and Church (2020) highlight the
synergies between adaptation planning under the UNFCCC’s National
Adaptation Plan process and conflict reduction. Discussing development
more broadly, Abrahams (2020) suggests three barriers to development
that incorporate conflict–climate risks: geographically disconnected
impacts and outcomes, the discourse of climate as a threat multiplier
(rather than underlying peace) and teleconnected risks occurring at
different scales. Effective approaches rely on understanding local power
dynamics and social relations (Sovacool 2018; Roth etal. 2019; Sapiains
etal. 2021) (high agreement, medium evidence).
7.4.5.3 Gender-Based Approaches to Peacebuilding
Gender-based approaches provide novel under-utilised pathways
to achieving sustainable peace (high confidence). Security council
resolutions have encouraged the incorporation of gender analysis into
peacebuilding and research has shown that taking into account the
gendered nature of networks and dialogues opens new avenues for
cooperation that are conflict sensitive (Dunn and Matthew, 2015),
creating potential for women’s rights and advocacy groups to be drivers
of peace (Céspedes-Báez, 2018). For example, women are working to
reduce climate vulnerability security risks in urban settings by entering
local politics and joining community-based organised and civil society
networks (Kellog, 2020). The gendered nature of vulnerability and
access to natural resources (Sections4.6.4, 4.7.5.3, 5.4.2.3, 5.5.2.6,
5.8.2.2; Cross-Chapter BoxGENDER in Chapter 18) will influence the
efficacy of interventions to prevent conflict or to build durable peace
(Pearse, 2017; Chandra etal., 2017; Fröhlich etal., 2018). However, this
understanding has not so far resulted in widespread employment of
gender-led analyses (Fröhlich and Gioli, 2015). This represents a key
opportunity for expansion of the solution space for climate-related
conflict. Analysis of peace processes more generally demonstrates
the benefits of women’s participation in peace processes for devising
strategies for building peace (Paffenholz, 2018; Cárdenas and Olivius,
2021) and for the durability of that peace (Shair-Rosenfield and Wood,
2017; Krause etal., 2018).
7.4.6 Climate Resilient Development Pathways
Climate resilient development is a set of trajectories that strengthens
sustainable development and efforts to eradicate poverty and reduce
inequalities while promoting fair and equitable reductions of GHG
emissions. Climate resilient development also serves to steer societies
towards low-carbon, prosperous and ecologically safer futures
(Chapter 1). All pathways to pursue climate resilient development
will involve balancing complex synergies and trade-offs (very high
confidence; Chapter 18). Pathways to climate resilient development
can be pursued simultaneously with recovering from the COVID-19
pandemic (Cross-Chapter BoxCOVID in Chapter 7; Ebi etal., 2021).
Meeting commitments against the following seven existing global
priorities would facilitate CRDPs and transformational futures for
health, well-being, conflict and migration (high agreement, medium
evidence):
i) Fully implementing the WHO Operational Framework for building
climate-resilient health systems (WHO, 2015b)
ii) Achieving Universal Health Coverage (UHC) under SDG 3 (good
health and well-being)
iii) Achieving net zero GHG emissions from healthcare systems and
services
iv) Achieving the SDGs more generally
v) Adopting mitigation policies and technologies that have significant
health co-benefits (see Cross-Chapter BoxHEALTH)
vi) Meeting the objectives of the Global Compact for Safe, Orderly and
Regular Migration
vii) Inclusive and integrative approaches to climate-resilient peace
These transformations map across all five of the system transitions
identified in Chapter 18: energy systems; land, ocean, and ecosystems;
urban and infrastructural systems; industrial systems; and societal
systems.
7.4.7.1 Fully Implementing the World Health Organization
Operational Framework
The WHO Operational Framework for building climate-resilient health
systems was designed to increase the capacity of health systems
and public health programming to protect health in an unstable and
changing climate (WHO, 2015b). The guidance defines a climate-
resilient health system as one that is capable to anticipate, respond
to, cope with, recover from and adapt to climate-related shocks and
stress, so as to bring sustained improvements in population health
despite an unstable climate. Full implementation of this framework has
the potential to achieve transformational adaptation; the fundamental
attributes of health systems would change to anticipate and effectively
manage the population health and healthcare risks of climate change.
This includes having the knowledge, capacity, tools and human and
financial resources for health systems to extend beyond soft limits to
adaptation.
The WHO framework outlines 10 key components (Figure7.15) that,
when achieved, will:
Guide professionals working in health systems and in health
determining sectors (e.g., water and sanitation, food and
agriculture, energy, and urban planning) to understand and
effectively prepare for the additional health risks posed by climate
variability and change
Identify the main health functions that need to be strengthened to
build climate resilience, and to use these to develop comprehensive
and practical plans (e.g., the health component of National
Adaptation Plans (H-NAP))
Support health decision makers to identify roles and responsibilities
to implement this plan for actors within and outside the formal
health sector
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Chapter 7 Health, Wellbeing and the Changing Structure of Communities
Achieving full implementation of the WHO Operational Framework
requires determination and commitment—with associated funding—
from the health community specifically and health-determining sectors
more generally. Identifying priority areas is an immediate step required
to commence this implementation process, which will vary across
different contexts. Active engagement with Communities of Practice to
share lessons and experiences would be a useful approach to support
national and sub-national efforts; examples of this already exist (e.g., the
Climate Change Community of Practice in Canada and the ‘weADAPT’
initiative under the auspices of the Stockholm Environment Institute).
Table7.9 summarises selected characteristics of health systems as they
might be under SSP1 (a world aiming to sustainable development),
SSP2 (a world continuing current trends) and SSP3 (a world with high
challenges to adaptation and mitigation), with systems under SSP1 being
most consistent with climate resilient development. The table highlights
the importance of investments that promote sustainable and resilient
development to decrease vulnerability, no matter the magnitude and
pattern of climate change. Adapting under SSP3 would be challenging
even under pathways of limited additional climate change.
Stress testing is an approach for evaluating the extent to which health
systems are prepared for a future different from today (Ebi etal., 2018a).
These desk-based exercises identify a desirable future outcome, such
as successfully managing an extreme heatwave, flood or storm with
characteristics outside the range of recent experiences. The exercises
move beyond identifying likely challenges from hazardous exposures
to specifying policies and measures that could be successful under a
different climate and development pathway. The exercises consider
socioeconomic and political factors that can influence the extent of
health system vulnerability and other factors that can affect health
system demands by impacting population health. Stress testing is
designed to identify conditions under which it would be difficult for
the health system to maintain its essential functions and to identify
interventions that could maintain essential system functions despite
climate-related shocks and stresses.
Ten components of the WHO operational framework for building climate resilient health systems,
with links to the building blocks of health systems.
C
L
I
M
A
T
E
R
E
S
I
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I
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N
C
E
Financing
Leadership &
governance
Health
workforce
Health
information
systems
Essential
medical
products &
technolologies
Service
delivery
H
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h
w
o
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o
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C
Financin
g
CLIMATE &
HEALTH FINANCING
LEADERSHIP &
GOVERNANCE
HEALTH
WORKFORCE
VULNERADBILITY,
CAPACITY &
ADAPTATION
ASSESSMENT
Building blocks
of health systems
INTEGRATED RISK
MONITORING & EARLY
WARNING
HEALTH & CLIMATE
RESEARCH
CLIMATE RESILIENT &
SUSTAINABLE
TECHNOLOGIES AND
INFRASTRUCTURE
MANAGEMENT OF
ENVIRONMENTAL
DETERMINANTS OF
HEALTH
CLIMATE-INFORMED
HEALTH
PROGRAMMES
EMERGENCY
PREPAREDNESS &
MANAGEMENT
Figure7.15 | Ten components of the WHO operational framework for building climate-resilient health systems with links to the building blocks of health
systems. Source: WHO (2015b).
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Health, Wellbeing and the Changing Structure of Communities Chapter 7
Table7.9 | Characteristics of future health systems under three SSPs; modified from Sellers and Ebi (2017).
SSP3 SSP2 SSP1
Basic characteristics
Reactive; failure to adapt; siloed information
channels and national governance; limited
partnerships
Incomplete planning; new information incorporated
as convenient; occasional partnerships
Proactive; adaptively managed; frequent
partnerships; inter-disciplinary
Leadership and
governance
Little focus at national and international levels
on climate change and health; minimal planning
conducted
Planning for climate change and health, but not
comprehensive and often side-tracked by other
issues
Strong climate change and health planning
apparatus, including health components of
national adaptation plans; regional/international
partnerships
Health workforce
Climate change and health not often incorporated
into training; few provisions for new training
programmes or funding for increase health worker
positions in climate change-relevant specialties;
health disparities not addressed
Climate change and health not systematically
incorporated into training; new training
programmes insufficient to fill gaps in demand;
limited attention to addressing health disparities
Systematic inclusion of climate change and health
in worker training; expansion of funding and
training; financing and incentive mechanisms to
address health disparities
Health information
systems
Assessments of vulnerability and adaptation rarely
conducted, if ever; information not useful for
planning; minimal risk monitoring or research
Vulnerability and adaptation assessments
occasionally conducted, but generally of poor
quality; early warnings incomplete; fiscal and
political constraints on research
Vulnerability and adaptation assessments regularly
conducted and used in planning; robust early
warning networks; research agenda focused on
vulnerable communities
Climate-resilient
and sustainable
technologies and
infrastructure
Facilities sited and constructed without climate
consideration incorporated; medical supply chains
not modified
Capital cost serves as a key factor in siting and
construction; increasing vulnerability of facilities
to shocks
Health infrastructure designed to be robust to
storms/floods, with redundant systems added to
ensure continuity of care
Service delivery
Policies to manage environmental health hazards
generally not followed; care practices not modified
to accommodate climate information; few changes
to emergency management procedures; health
inequities worsen
Environmental health policies are not robust;
marginal improvements in care practices; risk
assessments and communication inadequate; no
shift in health inequities
Policies to manage environmental health hazards
regularly reviewed; practitioners review care
practices and adjust as appropriate based on
local climate and health conditions; robust
communication tools developed; health service
improvements reduce health inequities
Climate and health
financing
Few funds devoted to climate change and health
activities, particularly in low- and middle-income
countries; few if any financing partnerships between
high-, low- and middle-income countries; very weak
regional and international coordinating bodies due
to funding constraints
High-income countries generally form robust
financing mechanisms; fiscal pressures in low- and
middle-income countries constrain their financing
abilities; financial partnerships formed across
countries, but financing often not robust; regional
and international coordinating bodies receive
inadequate funds
Robust funding streams for climate change and
health; climate change and health activities
receive continuing financial support; effective
financing partnerships; regional and international
coordinating bodies effectively funded
7.4.6.2 Achieving Universal Health Coverage Under SDG 3
(good health and well-being)
UHC is when all people have access to the health services they need,
when and where they need them, without financial hardship (WHO,
2021b). Achieving UHC is one of the targets in the SDGs. However,
climate change is threatening to undermine the achievement of UHC
through negative health outcomes and healthcare system disruptions
(Salas and Jha, 2019; Phillips et al., 2020; Kadandale et al., 2020;
Roa et al., 2020). Climate change adaptation and UHC progress
are closely linked to one another, as both may improve health and
achieve health equity (Salas and Jha, 2019). Supporting UHC is key
to securing population health under a changing climate as well as
addressing structural inequalities (Roos et al., 2021; Aleksandrova,
2020; Phillips etal., 2020). Many regions of the world with the highest
levels of vulnerability to the health impacts of climate change also
have low levels of UHC; an integrated approach to UHC planning that
incorporates climate change will have great benefits particularly in
improving health equity (Salas and Jha, 2019).
The COVID-19 pandemic has shown some countries taking positive steps
to achieving UHC. For example, Ireland nationalised healthcare for the
duration of the pandemic and many countries, including Australia, have
enhanced their telehealth services, which has enabled specific groups
to access health services, particularly those in rural and remote settings,
and has allowed continuous care to the community (Monaghesh and
Hajizadeh, 2020; Cross-Chapter BoxCOVID in Chapter 7).
7.4.6.3 Achieving Net Zero GHG Emissions from Healthcare
Systems and Services
The healthcare system is a core component of UHC, supporting
climate-resilient and environmentally sustainable healthcare facilities
(Corvalan et al., 2020). Health systems are large carbon polluters
and have the potential to look beyond traditional ‘green’ initiatives
towards a more fundamental, longer-term redesign of current
service models, with health practitioners participating actively in this
process (Charlesworth and Jamieson, 2018). In the largest and most
comprehensive accounting of national healthcare service emissions,
the UK’s National Health Service (NHS) quantified its health services’
emissions and identified that 62% came from the supply chain, 24%
from the direct delivery of care, 10% from staff commute and patient
and visitor travel, and 4% from private health and care services
commissioned by the NHS (Tennison etal., 2021).
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Chapter 7 Health, Wellbeing and the Changing Structure of Communities
The health sector has considerable opportunity to reduce its own
carbon footprint and by doing so would contribute to mitigation efforts
and help reduce health burdens associated with GHG emissions (Vidal
etal., 2014; Duane et al., 2019; Charlesworth and Jamieson, 2019;
Charlesworth etal., 2018; Guetter etal., 2018; Bharara etal., 2018;
Frumkin, 2018) (high confidence). The UK’s NHS has committed to
becoming the world’s first net zero national healthcare system. Other
examples of recent and ongoing initiatives include those undertaken
by the Kaiser Permanente and the Gundersen Clinics in the USA, Health
Care without Harm in the Asia Pacific region, and the Green Hospital
Initiative in New Delhi (Frumkin, 2018; Bharara etal., 2018).
7.4.6.4 Achieving the SDGs Would Increase Resilience in
Health-Determining Sectors and Contribute to Reducing
the Risks of Involuntary Displacement and Conflict
The SDGs are globally agreed objectives that integrate the economic,
environmental and social aspects of sustainable development to end
poverty, protect nature and ensure that all people enjoy peace and
prosperity. The SDGs were developed under the principle that the
goals are integrated and indivisible, such that progress in one goal
depends on progress in others (WHO, 2016b). Promoting health and
well-being is not the sole responsibility of the health sector; it is also
partially determined by strategies, policies and options such as poverty
reduction, promoting gender equality, ensuring all people enjoy
peace and prosperity, eliminating nutritional insecurity and ensuring
availability and sustainable management of water and sanitation
(Morton et al., 2019; Bennett et al., 2020). Unique themes in the
SDGs for health policy and systems research include social protection,
access to health services, stronger and more effective multi-sectoral
collaborations beyond the health sector to address the upstream
drivers of health and well-being, and participatory and accountable
institutions to strengthen civic engagement and local accountability
within health systems (Bennett etal., 2020).
For example, clean water, sanitation and hygiene are essential to
human health and well-being. Unsafe water and sanitation and a lack
of hygiene caused an estimated 870,000 associated deaths in 2016
(WHO, 2021c). Only 71% of the global population has access to safely
managed drinking water services; only 45% of the global population
has access to safely managed sanitation services; and 60% has basic
handwashing facilities in their home. About 25% of healthcare facilities
lack basic water services, exposing workers and patients to higher
infection risks. More than 80% of countries reported in 2018 that they
lacked sufficient funding to meet national WASH targets. As detailed in
Section7.2.2.2, Box7.3, Section7.3.1.4 and Section7.4.2.3, the burden
of climate-sensitive WBDs would be reduced if WASH targets were met.
WHO developed a Global Action Plan for Healthy Lives and Well-Being
for All that brings together multi-lateral health, development and
humanitarian agencies to support countries in accelerating progress
towards the health-related SDGs (WHO, 2021c). Themes include
sustainable financing to reduce unmet needs for services, community
and civil society engagement to generate knowledge to inform
policymaking and health responses, addressing the socioenvironmental
determinants of health, ensuring health and humanitarian services are
available in fragile and vulnerable settings, research and development,
and greater implementation of digital health delivery. In 2020,
enhanced collaboration through the Global Action Plan provided
support for an equitable recovery from the COVID-19 pandemic in,
for example, Lao People’s Democratic Republic, Pakistan, Tajikistan,
Somalia, South Sudan, Malawi, Nepal and Columbia, highlighting the
potential for multi-sectoral integration of economic, environmental
and social aspects of sustainable development to maintain essential
health services and core public health functions during shocks and
stresses (WHO, 2021a).
Meeting the SDGs also contributes towards reducing involuntary
displacement and conflict, as assessed in Sections7.4.6.6 and 7.4.6.7.
7.4.6.5 Adopting Mitigation Policies and Technologies that
Have Significant Health Co-benefits
Substantial co-benefits from climate action can result from investing
in health systems, infrastructure, water and sanitation, clean energy,
affordable healthy diets, low-carbon housing, public transport,
improved air quality, and social protection. These benefits are in
addition to the avoided health impacts associated with climate change
(see Cross-Chapter BoxHEALTH in Chapter 7).
7.4.6.6 International Policy Frameworks for Migration that
Contribute to Climate Resilient Development
Climate-related migration, displacement and immobility in coming
decades will coincide with global and regional demographic changes
that will produce a widening distinction between high-income
countries that have aging, slow-growing (or in some countries,
shrinking) population numbers and low-income countries that have
rapidly growing, youthful populations. Given this dynamic, coordinated
national and international strategies that integrate migration and
displacement considerations with wider adaptation and sustainable
development policies may contribute to climate resilient development.
Since AR5, the international community has established a number
of agreements and initiatives that, with continued pursuit and
implementation, would create potential for climate-related migration
to be a positive contribution towards adaptive capacity-building and
sustainable development more broadly (Warner, 2018).
The 2018 Global Compact for Safe, Orderly and Regular Migration
provides an important opportunity for planning for and responding
to future climate-related migration and displacement (Kälin, 2018).
Among its 23 objectives, the Compact explicitly encourages the
international community to implement migration policies that facilitate
voluntary migration and actively prepare for involuntary displacements
due to climate change, especially in low- and middle-income countries.
The Compact’s objectives include reducing barriers to legal and safe
migration, and facilitating the freer flow of remittances between sending
and receiving communities. By doing so the Compact aims to increase
the potential for migration to make positive contributions to sustainable
development and to adaptive capacity-building. It also contains specific
provisions pertaining to climate- and disaster-related migration and
displacement. Objective 2 of the Compact aims at reducing drivers
of involuntary or low-agency migration and recommends that states
establish systems for sharing information on environmental migration,
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Health, Wellbeing and the Changing Structure of Communities Chapter 7
develop climate adaptation and resilience strategies harmonised
at sub-regional and regional levels, and cooperate on disaster risk
prevention and response. Other objectives in the Compact relevant
to climate-related migration include Objective 5 (increasing pathways
for regular migration) and Objective 19 (facilitating migrants’ ability
to contribute to sustainable development). Objective 18, which links
migration with skills development, is consistent with the ‘migration with
dignity’ approach to displacement risks (McNamara, 2015; Kupferberg,
2021). The 2018 Global Compact on Refugees observes that climate
hazards increasingly interact with the drivers of refugee movements.
The guidelines this Compact provides to governments regarding actions
for addressing the causes of refugee movements and considerations for
assisting and supporting refugees are useful for governments seeking
guidance for all forms of displacement more generally, including
displacement linked to climate change.
Pursuant to the Paris Agreement, a task force was struck by the
Warsaw International Mechanism to make recommendations to the
Conference of the Parties to the UNFCCC on how to reduce the risks
of climate-related displacement. Its 2018 report recommended that
parties work towards development of national legislation, cooperate
on research, strengthen preparedness, integrate mobility into wider
adaptation plans, work towards safe and orderly migration, and
provide assistance to people internally displaced for climate-related
reasons. Such recommendations dovetail strongly with the objectives
of the Compacts on Migration and Refugees as well as the Sendai
Framework for DRR and the 2030 SDGs. The SDGs, which include
multiple goals and targets in which migration plays an explicit role
in fostering development (Nurse, 2019), may be seen as completing
the international policy arrangements necessary for addressing future
climate-related migration and displacement.
7.4.6.7 Inclusive and Integrative Approaches to Climate-
Resilient Peace
CRDPs to reduce conflict risk rely on a shift in perspective from framings
around resource scarcity and security to sustainable natural resource
governance and peace (Brauch et al., 2016; Barnett, 2018; Dresse
et al., 2018; Day and Caus, 2020). Recognising that conflict results
from underlying vulnerabilities, development that reduces vulnerability
offers the best win-win option for building sustainable, climate-
resilient peace rather than specific security-focused interventions (high
confidence). To this end, meeting the SDGs represents an unambiguous
path to reducing conflict risk in a climate-changed world (Singh and
Chudasama, 2021). There is growing acceptance in the development
community, despite reservations about the securitisation of climate,
that instability and conflict exacerbated by climate change has the
potential to undermine development gains (Casado-Asensio et al.,
2020; Day and Caus, 2020).
Core to achieving climate-resilient peace are new ways of working that
involve cross-issue and cross-sectoral collaboration and integration as
a default to policy and programming. The Security Council Resolution
1325 Women and peace and security (S/RES/1325 (2000)) and the
Sustaining Peace Agenda (A/RES/70/262 (2016)) are notable examples
of this. The 2020 UNEP report on gender and security recommends
integrated policy frameworks, better financing to strengthen women’s
roles in peacebuilding, integrated programme design, and further
research on gender, climate and security linkages. Inclusive approaches
recognise that much of the vulnerability that drives conflict risk
is generated by existing inequality and marginalisation of large
proportions of the population—for example women and youth—and
that peace cannot be achieved without their needs being taken into
account and without their participation in peace processes (Mosello
etal., 2021). Diverse and inclusive partnerships also require ways to
better engage local-level participation, and improve understanding of
how to build consensus through human rights-based approaches that
recognize non-violent conflict and protest to be potentially positive
and constructive elements of transformational approaches to building
resilience (Nursey-Bray, 2017; Ensor etal., 2018; Schipper etal., 2021).
Addressing the lack of participation of researchers and experts from
countries most at risk of conflict in many climate-related conflict and
peacebuilding assessments and initiatives could also support this
objective. There is an increasing focus on the role of environmental
defenders in highlighting violations and gaps in state obligations
through non-violent protest (Butt etal., 2019; Scheidel etal., 2020).
CRDPs for sustainable peace also require different ways of gathering
intelligence and informing conflict risk. Dynamics that affect such
risks exist across scales from the local to the regional, and require
response in a transboundary manner. There is increasing emphasis on
engaging local stakeholders and diverse partnerships to inform context
appropriate measures and better policy coordination (Bremberg etal.,
2019; Tshimanga et al., 2021; Abrahams, 2020). The UN’s Climate
Security Mechanism, working across three UN departments, takes an
integrated approach to analyse and support timely and appropriate
responses to conflict risk, focusing on risk assessments and early
warning systems to aid conflict prevention, climate-informed peace and
security activities and conflict-sensitive development, and to promote
inter-sectoral cooperation, partnership and information sharing (DPPA
etal., 2020). There is already acknowledgement that adaptation needs
to be effectively monitored so that maladaptation can be avoided
(Eriksen etal., 2021). Here, academic research, which until now has
predominantly focused on understanding the causal relationship
between conflict and climate, could contribute to advancing the
monitoring and evaluation of climate-resilient peacebuilding initiatives
(Mach etal., 2020; Gilmore etal., 2018).
7
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Chapter 7 Health, Wellbeing and the Changing Structure of Communities
Cross-Chapter BoxHEALTH | Co-benefits of Climate Actions for Human Health, Well-Being and
Equity
Authors: Cristina Tirado (USA/Spain, Chapter 7); Robbert Biesbroek (Netherlands, Chapter 13); Mark Pelling (United Kingdom, Chapter 6);
Jeremy Hess (USA, Chapter 7); Felix Creutzig (Germany, WGIII); Rachel Bezner Kerr (Canada/USA, Chapter 5); Siri Eriksen (Norway, Chapter
18); Diarmid Campbell-Lendrum (United Kingdom, Chapter 7); Elisabeth Gilmore (USA/Canada, Chapter 14); Maria Figueroa (Denmark/
Venezuela, WGIII); Nathalie Hilmi (Monaco, Chapter 18); Peter Newman (Australia, WGIII); Sebastian Mirasgedis (Greece, WGIII); Sharma
Rohit (India); Yamina Saheb (France/Algeria, WGIII); Gerardo Sanchez Martinez (Spain); Peter Smith (United Kingdom, WGIII); Adrian Leip
(Italy, WGIII); Dhar Subash (Denmark/India, WGIII); Chris Trisos (South Africa, Chapter 9); Mercedes Bustamante (Brazil, WGIII); Luisa
Cabeza (Spain, WGIII); Diana Urge-Vorsatz (Hungary, WGIII)
Achieving the Paris Agreement and SDGs can result in low-carbon, healthy, resilient and equitable societies with high well-being for all (very
high confidence) (Alfredsson etal., 2018; O’Neill etal., 2018). Given the overlap in sources of greenhouse gases (GHGs) and co-pollutants
in energy systems, strategies that pursue GHG emission reductions and improvements in energy efficiency hold significant potential health
co-benefits through air pollution emission reductions (high confidence) (Gao etal., 2018). Air quality improvements alone can substantially
offset, or most likely exceed, mitigation costs at the societal level (Schucht etal., 2015; Chang etal., 2017; Markandya etal., 2018; Vandyck
etal., 2018; Peng etal., 2017; Woodward etal., 2019; Sampedro etal., 2020; Xie etal., 2018). Pursuit of a mitigation pathway compatible
with warming of +1.5°C with associated cleaner air, avoided extreme events and improved food security and nutrition could result in 152
± 43million fewer premature deaths worldwide between 2020 and 2100 compared with a business-as-usual scenario (Shindell etal.,
2018). Reaching the Paris Agreement could result in an annual reduction of 1.18million air pollution-related deaths, 5.86million diet-
related deaths and 1.15million deaths due to physical inactivity across nine major economies by 2040 (Hamilton etal., 2021). In Europe,
a mitigation scenario compatible with RCP2.6 could reduce total pollution costs, mostly from PM2.5, by 84%, with human health benefits
equal to more than Euro 1 trillion over five years (Scasny etal., 2015). In the EU, ambitious climate mitigation policies could reduce years
of lost life due to fine particulate matter (PM) from over 4.6million in 2005 to 1million in 2050, reduce ozone-related premature deaths
from 48,000 to 7,000 and generate health benefits of Euro 62billion yr
–1
in 2050 (Schucht etal., 2015).
However, there may be significant trade-offs between mitigation and other societal goals (Dong etal., 2019; Gao et al., 2018). In
some scenarios, mitigation policies consistent with the NDCs may slow poverty reduction efforts (Campagnolo and Davide, 2019) with
implications for health. A framework of ‘co-impacts’ that assumes neither a general beneficial nature of all implications from mitigation
policy nor a hierarchy between climate and other types of benefits, may be more appropriate (Ürge-Vorsatz etal., 2014; Cohen etal., 2017).
Transitioning to affordable clean energy sources for all presents opportunities for substantial well-being, health, and equity co-benefits
(high confidence) (Gibon etal., 2017; Lacey etal., 2017; Peng etal., 2018; Vandyck etal., 2018; Williams etal., 2018). Residential solid fuel
use affects health and degrades indoor air quality for up to 3.1billion people in low- and middle-income countries (WHO, 2016b; Wang
etal., 2017a). Adherence to planned emission reductions from the Paris Agreement related to renewables could subsequently improve air
quality and prevent 71,000–99,000 premature deaths annually by 2030 (Vandyck etal., 2018). This effect increases with a 2°C pathway,
with 0.7–1.5million premature deaths avoided annually by 2050 (Vandyck etal., 2018). Co-benefits are also observed at national and
regional levels. For instance, China could expect 55,000–69,000 averted deaths in 2030 if it transitioned to a half-decarbonised power
supply for its residential and vehicle sectors (Peng etal., 2018).
Investing in universal basic infrastructure, including sanitation, clean drinking water, drainage, electricity, and land-rights, can transform
development opportunities, increase adaptive capacity, and reduce vulnerability to climate-related risks (high agreement, high evidence).
Transformative approaches that reduce climate-related risks and deliver enhanced social inclusion and development opportunities for
the urban poor are most likely where local governments act in partnership with local communities and other civil society actors (high
confidence) (Chapter 6, sections 6.1, 6.3, 6.4).
Rapid urbanisation offers a time-limited opportunity to work at scale towards transformational adaptation and climate resilient
development (medium evidence, high agreement). Multi-level leadership, institutional capacity and financial resources to support
inclusive adaptation in the context of multiple pressures and inter-connected risks can help ensure that the additional 2.5billion people
projected to live in urban areas by 2050 are less exposed to climate-related hazards and contribute less to global warming (high
confidence) (Chapter 6, sections 6.1, 6.3, 6.4). Integrating low-carbon, inclusive adaptation into infrastructure investment driven by rapid
urban population growth and COVID-19 recovery can accelerate co-benefits (Chapter 6).
Urban planning that combines clean, affordable public transportation, shared clean vehicles and accessible active transportation modes
can improve air quality and contribute to healthy, equitable societies and higher well-being for all. Stimulating active mobility (walking
and bicycling) can bring physical and mental health benefits (high confidence) (Chapter 6; Rojas-Rueda etal., 2016; Avila-Palencia etal.,
7
1125
Health, Wellbeing and the Changing Structure of Communities Chapter 7
2018; Gascon etal., 2019; Hamilton etal., 2021). The health gains from active mobility outweigh traffic-related injuries due to a decreased
incidence of chronic diseases (Ahmad etal., 2017; Maizlish etal., 2017; Tainio etal., 2017; Woodcock etal., 2018).
Urban green and blue spaces contribute to climate change adaptation and mitigation and improve physical and mental health and
well-being (high confidence) (Hansen 2017; EC, 2018; WHO, 2018a; Rojas-Rueda etal. 2019; 13.7.3, WGII; 6. WGII; 8.4 WGIII). Urban
green infrastructure including urban gardens, can bring benefits to social cohesion, mental health and well-being and reduce the health
impacts of heatwaves by decreasing temperatures, thus reducing inequities in exposure to heat stress for low income, marginalised
groups (Hoffman etal., 2020; Hoffmann etal., 2020; Chapter 5 section 5.12.5; Chapter 6; Chapter 7 section 7.4; Chapter 13 section 13.7).
The trade-offs of increasing urban green and blue spaces include potential public health risks related to increased vectors or hosts for
infectious diseases, toxic algal blooms, drowning and aeroallergens (Choi etal., 2021; Stewart-Sinclair etal., 2020; Chapter 6).
Climate adaptation and mitigation policies in the building sector offer multiple well-being and health co-benefits (high confidence)
(Diaz-Mendez etal., 2018; Macnaughton etal., 2018; Chpater 3 section 3.6.2). Leadership in Energy and Environmental Design (LEED)
certified buildings in the USA, Brazil, China, India, Germany and Turkey saved an estimated USD 7.5billion in energy costs and averted
33 Mt of CO
2
from 2000–2016 (Macnaughton etal., 2018). These measures can increase health benefits through better indoor air quality,
reduction of the heat island effect, improved social well-being through energy poverty alleviation, creation of new jobs, increased
productive time and income, increased thermal comfort and lighting indoors and reduced noise impact (Smith etal., 2016; McCollum
etal., 2018; Thema etal., 2017; Mirasgedis etal., 2014; Alawneh etal., 2019; Diaz-Mendez etal., 2018). The value of these multiple co-
benefits associated with climate actions in buildings is equal to or greater than the costs of energy savings (Ürge-Vorsatz etal., 2016;
Payne etal., 2015; Chapter 14 section 14.4.5).
Shifting to sustainable food systems that provide affordable, diverse and plant-rich diets with moderate quantities of GHG-intensive
animal protein can bring health co-benefits and substantially reduce GHG emissions, especially in high income countries and where ill
health related to overconsumption of animal-based products is prevalent (very high confidence) (Chapter 5 section 5.12.6; Chapter 7
section 7.4, Chapter 13 section 13.5; Springmann etal., 2018c; IPCC, 2019b; Clark and Tilman, 2017; Poore and Nemecek, 2018; Hayek
etal., 2021). Transforming the food system by limiting the demand for GHG-intensive animal foods, reducing food over-consumption and
transitioning to nutritious, plant-rich diets can have significant co-benefits to health (high confidence) (Hedenus etal., 2014; Ripple etal.,
2014; Tirado, 2017; Springmann etal., 2018c; IPCC, 2018; IPCC, 2019a; IPCC, 2019b; Nelson etal., 2016; Willett etal., 2019; Tilman and
Clark, 2014; Green etal., 2015; Springmann etal., 2016b; Springmann etal., 2018b; Springmann etal., 2018a; Springmann etal., 2018c;
Milner etal., 2015; Milner etal., 2017; Farchi etal., 2017; Song etal., 2017; Willett etal., 2019). Reduction of red meat consumption
reduces the risk of cardiovascular disease (CVD) and colorectal cancer; the consumption of more fruits and vegetables can reduce the risk
of CVD, type II diabetes, cancer and all causes of mortality (Tilman and Clark, 2014; Sabate and Soret, 2014; Willett etal., 2019; Chapter
7 section 7.4; Chapter 5 section 5.12.5). Globally, it is estimated that transitioning to more plant-based diets—in line with World Health
Organization (WHO) recommendations on healthy eating—could reduce global mortality by 610% and food-related GHG emissions by
2970% by 2050 (Springmann etal., 2016b). There are limitations in accessibility of affordable of healthy and diverse diets for all
(Springmann etal., 2020) and trade-offs such as the potential increase of GHG emissions from producing healthy and diverse diets in
low- and medium-income countries (Semba etal., 2020). Agroecological approaches have mitigation and adaptation potential and
deliver ecosystem services, biodiversity, livelihoods and benefits to nutrition, health and equity (Rosenstock etal., 2019; Bezner Kerr etal.,
2021; Chapter 5 sections 5.4.4, 5.14.1; Chapter 13 section 13.5; Chapter 14 section 14.4.4).
Cross-Chapter BoxHEALTH (continued)
7
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Chapter 7 Health, Wellbeing and the Changing Structure of Communities
Frequently Asked Questions
FAQ 7.1 | How will climate change affect physical and mental health and well-being?
Climate change will affect human health and well-being in a variety of direct and indirect ways that depend on
exposure to hazards and vulnerabilities that are heterogeneous and vary within societies, and that are influenced
by social, economic and geographical factors and individual differences (see Figure FAQ7.1.1). Changes in the
magnitude, frequency and intensity of extreme climate events (e.g., storms, floods, wildfires, heatwaves and dust
storms) will expose people to increased risks of climate-sensitive illnesses and injuries and, in the worst cases, higher
mortality rates. Increased risks for mental health and well-being are associated with changes caused by the impacts
of climate change on climate-sensitive health outcomes and systems (see FigureFAQ7.1.2). Higher temperatures and
changing geographical and seasonal precipitation patterns will facilitate the spread of mosquito- and tick-borne
diseases, such as Lyme disease and dengue fever, and water- and food-borne diseases. An increase in the frequency
of extreme heat events will exacerbate health risks associated with cardiovascular disease and affect access to
freshwater in multiple regions, impairing agricultural productivity and increasing food insecurity, undernutrition
and poverty in low-income areas.
Pathways from hazards, exposure and vulnerabilities to climate change impacts on health outcomes
and health Systems
Vulnerability
Exposure
Hazard
Risk
Age
Gender
Mobility
Access to care
Socio-economic status
Pre-existing conditions
Characteristics of health system
Outdoor employment
Housing quality
Location/local geography
Livelihood type
Heat, drought
Floods
Storms
Vector spread
CLIMATE SENSITIVE OUTCOMES
- Adverse health (VBD, WBD, infectious disease,
heat-related illness, mental health, under nutrition)
- Migration & displacement
- Conflicts
SYSTEM IMPACTS
Health system (patient loads, emergency responses, costs)
- Food systems
- Livelihood systems
IMPACTS
FigureFAQ7.1.1 | Pathways from hazards, exposure and vulnerabilities to climate change impacts on health outcomes and health systems.
WBD: waterborne disease, VBD: Vector-borne disease, and FBD: Food-borne disease.
7
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Health, Wellbeing and the Changing Structure of Communities Chapter 7
Climate change impacts on mental health and adaptation responses
2
1
Hazard
Acute events
(e.g. storms, floods, wildfires,
extreme heat)
Chronic changes
(e.g. drought, sea level rise,
sea ice loss, changing climate
normals)
Vulnerability
Pre-existing health conditions
Socio-economic inequities
Gender
Age
Occupation
Exposure
Direct exposure(s)
Indirect exposure(s)
(e.g. displacement, food systems
disruption, occupational loss)
Vicarious exposure(s)
(e.g. observed experiences of others,
media depictions of climate change)
Key adaptation responses
Scale of adaptation
Institutional
State and non-state actors:
effective mental health systems,
planning and preparedness, informed
policies, early intervention
Local governments:
planning, design, green infrastructure
Community
- Supportive social networks, effective
information channels
Individuals
- awareness, preparedness, mental
health support, nature-based therapy
3
4
Risks to mental health and wellbeing
Mental illness
[e.g., PTSD, depression, suicide]
Diminished wellbeing
[e.g., stress, climate anxiety, cognitive
impairment )
Diminished social relations
[e.g., loss of culture, interpersonal violence)
5
2. Vulnerability
Physiological factors
Social factors
3.Exposure
Direct exposure(s)
Indirect exposure(s)
Vicarious exposure(s)
4. Response
Institutional
Community
Individuals
1. Hazard
Acute events
Chronic changes
5. Risks
to mental health
and wellbeing
FigureFAQ7.1.2 | Climate change impacts on mental health and key adaptation responses.
PTSD: Post traumatic stress disorder.
Box FAQ7.1 (continued)
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Chapter 7 Health, Wellbeing and the Changing Structure of Communities
Frequently Asked Questions
FAQ 7.2 | Will climate change lead to wide-scale forced migration and involuntary displacement?
Climate change will have impacts on future migration patterns that will vary by region and over time, depending
on the types of climate risks people are exposed to, their vulnerability to those risks and their capacity—and the
capacity of their governments—to adapt and respond. Depending on the range of adaptation options available,
households may use migration as a strategy to adapt to climate risks, often through labour migration. The most
common drivers of climate-related displacement are extreme weather events, floods and droughts, especially when
these events cause severe damage to homes, livelihoods and food systems. Rising sea levels will present a new
risk for communities situated in low-lying coastal areas and small island states. The greater the scale of future
warming and extreme events, the greater the potential scale of future, involuntary climate-related migration and
displacement.Progress towards achieving the Sustainable Development Goals (SDGs) has strong potential to reduce
future involuntary climate-related migration and displacement.
Frequently Asked Questions
FAQ 7.4 | What solutions can effectively reduce climate change risks to health, well-being, forced migration and
conflict?
The solution space includes policies, strategies and programmes that consider why, how, when and who should be
involved to sustainably adapt to climate change. Effectively preparing for and managing the health risks of climate
change requires considering the multiple interacting sectors that affect population health and effective functioning
of health systems. Considering the close inter-connections between health, migration and conflict, interventions
that address climate risks in one area often have synergistic benefits in others. For example, conflicts often result
in large numbers of people being involuntarily displaced and facilitate the spread of climate-sensitive diseases;
tackling the underlying causes of vulnerability and exposure that generate conflict reduces risks across all areas.
A key starting point for health and well-being is strengthening public health systems so that they become more
climate resilient, which also requires cooperation with other sectors (water, food, sanitation, transportation, etc.) to
ensure appropriate funding and progress on sustainable development goals. Interventions to enhance protection
against specific climate-sensitive health risks could reduce morbidity and mortality and prevent many losses and
damages (FigureFAQ7.4.1). These range from malaria net initiatives, vector control programmes, health hazard
(syndromic) surveillance and early warning systems, improving access to water, sanitation and hygiene (WASH), heat
action plans (HAPs), behavioural changes and integration with disaster risk reduction (DRR) and response strategies.
More importantly, climate resilient development pathways (CRDPs) are essential to improve overall health and
well-being, reduce underlying causes of vulnerability and provide a framework for prioritising mitigation and
Frequently Asked Questions
FAQ 7.3 | Will climate change increase the potential for violent conflict?
Climate hazards have affected armed conflict within countries but the observed influence of climate is small relative
to socioeconomic, political and cultural factors. Adverse impacts of climate change threaten to increase poverty
and inequality, undermine progress in meetings Sustainable Development Goals (SDGs) and place strain on civil
institutions—all of which are factors that contribute to the emergence or worsening of civil unrest and conflict.
Climate change impacts on crop productivity and water availability can function as a ‘risk multiplier’ for conflict in
areas that are already politically and/or socially fragile and, depending on circumstances, could increase the length
or the nature of an existing conflict. Institutional initiatives within or between states to protect the environment
and manage natural resources can serve simultaneously as mechanisms for engaging rival groups and adversaries
to cooperate in policymaking and peacebuilding.
7
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Health, Wellbeing and the Changing Structure of Communities Chapter 7
Frequently Asked Questions
FAQ 7.5 | What are some specific examples of actions taken in other sectors that reduce climate change risks in the
health sector?
Many actions taken in other sectors to address the risks of climate change can lead to benefits for health and
well-being. Adaptive urban design that provides greater access to green and natural spaces simultaneously enhances
biodiversity, improves air quality and moderates the hydrological cycle; it also helps reduce health risks associated
with heat stress and respiratory illnesses, and mitigates mental health challenges associated with congested
urban living. Transitioning away from internal-combustion vehicles and fossil fuel-powered generating stations
to renewable energy mitigates greenhouse gas emissions, improves air quality and lowers the risks of respiratory
illnesses. Policies and designs that facilitate active urban transport (walking and bicycling) increase efficiency in
that sector, reduce emissions, improve air quality and generate physical and mental health benefits for residents.
Improved building and urban design that foster energy efficiency improve indoor air quality and reduce risks of
heat stress and respiratory illness. Food systems that emphasise healthy, plant-centred diets reduce emissions in the
agricultural sector while helping in the fight against malnutrition.
adaptation options that support sustainable development. Transformative changes in key sectors including water,
food, energy, transportation and built environments offer significant co-benefits for health.
Adaptation responses to climatic risks
Adaptation in
other sectors
Vulnerability
Exposure
Hazard
Risk
Sustainable
livelihoods
Ch. 8
Biodiversity
Ch. 2; CCP 1
Ocean &
coastal systems
Ch. 3
Urban
systems
Ch. 6
Water & food
Ch. 4, 5
Adaptation responses
Can reduce vulnerability
Can reduce vulnerability
Can reduce exposure
Can reduce exposure
Health sector
adaptation
FigureFAQ7.4.1 | Solution space for adaptation to climate change in health and other sectors.
FAQ7.4 (continued)
7
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Chapter 7 Health, Wellbeing and the Changing Structure of Communities
Acknowledgements
The Lead Autors wish to recognize with thanks the research assistance
and editorial assistance provided by Alyssa Gatt and Edi Cadham of
Wilfrid Laurier University (Canada).
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